Overview

Dataset statistics

Number of variables27
Number of observations474417
Missing cells1770737
Missing cells (%)13.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory94.6 MiB
Average record size in memory209.0 B

Variable types

Numeric15
Categorical11
Boolean1

Warnings

slug has a high cardinality: 474415 distinct values High cardinality
name has a high cardinality: 474415 distinct values High cardinality
released has a high cardinality: 8631 distinct values High cardinality
updated has a high cardinality: 241644 distinct values High cardinality
website has a high cardinality: 46969 distinct values High cardinality
platforms has a high cardinality: 5148 distinct values High cardinality
developers has a high cardinality: 213723 distinct values High cardinality
genres has a high cardinality: 1968 distinct values High cardinality
publishers has a high cardinality: 45452 distinct values High cardinality
rating is highly correlated with rating_topHigh correlation
rating_top is highly correlated with ratingHigh correlation
ratings_count is highly correlated with reviews_count and 1 other fieldsHigh correlation
reviews_count is highly correlated with ratings_count and 1 other fieldsHigh correlation
added_status_yet is highly correlated with added_status_ownedHigh correlation
added_status_owned is highly correlated with added_status_yetHigh correlation
added_status_beaten is highly correlated with ratings_count and 1 other fieldsHigh correlation
metacritic has 469684 (99.0%) missing values Missing
released has 24199 (5.1%) missing values Missing
website has 409376 (86.3%) missing values Missing
developers has 8366 (1.8%) missing values Missing
genres has 103185 (21.7%) missing values Missing
publishers has 333384 (70.3%) missing values Missing
esrb_rating has 418553 (88.2%) missing values Missing
playtime is highly skewed (γ1 = 181.4873355) Skewed
achievements_count is highly skewed (γ1 = 45.1069999) Skewed
ratings_count is highly skewed (γ1 = 41.89712863) Skewed
game_series_count is highly skewed (γ1 = 22.75979028) Skewed
reviews_count is highly skewed (γ1 = 41.98398272) Skewed
added_status_yet is highly skewed (γ1 = 27.88984876) Skewed
added_status_owned is highly skewed (γ1 = 24.63380046) Skewed
added_status_beaten is highly skewed (γ1 = 50.7065118) Skewed
added_status_toplay is highly skewed (γ1 = 85.48676318) Skewed
added_status_dropped is highly skewed (γ1 = 38.93530996) Skewed
added_status_playing is highly skewed (γ1 = 72.95285179) Skewed
slug is uniformly distributed Uniform
name is uniformly distributed Uniform
id has unique values Unique
rating has 462423 (97.5%) zeros Zeros
playtime has 451355 (95.1%) zeros Zeros
achievements_count has 456734 (96.3%) zeros Zeros
ratings_count has 437847 (92.3%) zeros Zeros
suggestions_count has 37455 (7.9%) zeros Zeros
game_series_count has 471586 (99.4%) zeros Zeros
reviews_count has 437152 (92.1%) zeros Zeros
added_status_yet has 450434 (94.9%) zeros Zeros
added_status_owned has 415331 (87.5%) zeros Zeros
added_status_beaten has 447076 (94.2%) zeros Zeros
added_status_toplay has 446474 (94.1%) zeros Zeros
added_status_dropped has 450536 (95.0%) zeros Zeros
added_status_playing has 464939 (98.0%) zeros Zeros

Reproduction

Analysis started2021-03-07 01:06:03.290474
Analysis finished2021-03-07 01:07:45.209326
Duration1 minute and 41.92 seconds
Software versionpandas-profiling v2.10.0
Download configurationconfig.yaml

Variables

id
Real number (ℝ≥0)

UNIQUE

Distinct474417
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean266884.0003
Minimum1
Maximum525551
Zeros0
Zeros (%)0.0%
Memory size3.6 MiB
2021-03-06T17:07:45.456351image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25068.8
Q1133664
median267945
Q3406010
95-th percentile501650.2
Maximum525551
Range525550
Interquartile range (IQR)272346

Descriptive statistics

Standard deviation154567.8116
Coefficient of variation (CV)0.5791572797
Kurtosis-1.246638742
Mean266884.0003
Median Absolute Deviation (MAD)136203
Skewness-0.02453904388
Sum1.266143068 × 1011
Variance2.389120839 × 1010
MonotocityNot monotonic
2021-03-06T17:07:45.600394image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20471
 
< 0.1%
206411
 
< 0.1%
165471
 
< 0.1%
308841
 
< 0.1%
288371
 
< 0.1%
267901
 
< 0.1%
247431
 
< 0.1%
63121
 
< 0.1%
42651
 
< 0.1%
22181
 
< 0.1%
Other values (474407)474407
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
ValueCountFrequency (%)
5255511
< 0.1%
5255481
< 0.1%
5255471
< 0.1%
5255461
< 0.1%
5255451
< 0.1%

slug
Categorical

HIGH CARDINALITY
UNIFORM

Distinct474415
Distinct (%)100.0%
Missing2
Missing (%)< 0.1%
Memory size3.6 MiB
head-goal
 
1
project-suburbion
 
1
attack-of-the-shell
 
1
dawn-of-discovery-harbor
 
1
flight-world-simulator
 
1
Other values (474410)
474410 

Length

Max length50
Median length16
Mean length18.33913135
Min length1

Characters and Unicode

Total characters8700359
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474415 ?
Unique (%)100.0%

Sample

1st rowdgeneration-hd
2nd rowg-prime
3rd rowland-sliders
4th rowpixel-gear
5th rowgods-and-idols
ValueCountFrequency (%)
head-goal1
 
< 0.1%
project-suburbion1
 
< 0.1%
attack-of-the-shell1
 
< 0.1%
dawn-of-discovery-harbor1
 
< 0.1%
flight-world-simulator1
 
< 0.1%
wave-race-64-19961
 
< 0.1%
fight-in-space1
 
< 0.1%
color-bump1
 
< 0.1%
in-development1
 
< 0.1%
planterra1
 
< 0.1%
Other values (474405)474405
> 99.9%
(Missing)2
 
< 0.1%
2021-03-06T17:07:48.401068image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9
 
< 0.1%
escape4
 
< 0.1%
23
 
< 0.1%
darkarta-a-broken-hearts-quest-collectors-edition2
 
< 0.1%
think2
 
< 0.1%
chronicles-of-a-dark-lord-episode-1-tides-of-fate2
 
< 0.1%
reed2
 
< 0.1%
surface-alone-in-the-mist-a-hidden-object-mystery2
 
< 0.1%
tron2
 
< 0.1%
game-012
 
< 0.1%
Other values (474314)474385
> 99.9%

Most occurring characters

ValueCountFrequency (%)
-983369
 
11.3%
e835498
 
9.6%
a660662
 
7.6%
r559796
 
6.4%
o554086
 
6.4%
t541085
 
6.2%
i517309
 
5.9%
s480340
 
5.5%
n456219
 
5.2%
l374880
 
4.3%
Other values (28)2737115
31.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7580548
87.1%
Dash Punctuation983369
 
11.3%
Decimal Number132004
 
1.5%
Connector Punctuation4438
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
e835498
 
11.0%
a660662
 
8.7%
r559796
 
7.4%
o554086
 
7.3%
t541085
 
7.1%
i517309
 
6.8%
s480340
 
6.3%
n456219
 
6.0%
l374880
 
4.9%
c297302
 
3.9%
Other values (16)2303371
30.4%
ValueCountFrequency (%)
234236
25.9%
022725
17.2%
121647
16.4%
316487
12.5%
49075
 
6.9%
97272
 
5.5%
85636
 
4.3%
55276
 
4.0%
74833
 
3.7%
64817
 
3.6%
ValueCountFrequency (%)
-983369
100.0%
ValueCountFrequency (%)
_4438
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7580548
87.1%
Common1119811
 
12.9%

Most frequent character per script

ValueCountFrequency (%)
e835498
 
11.0%
a660662
 
8.7%
r559796
 
7.4%
o554086
 
7.3%
t541085
 
7.1%
i517309
 
6.8%
s480340
 
6.3%
n456219
 
6.0%
l374880
 
4.9%
c297302
 
3.9%
Other values (16)2303371
30.4%
ValueCountFrequency (%)
-983369
87.8%
234236
 
3.1%
022725
 
2.0%
121647
 
1.9%
316487
 
1.5%
49075
 
0.8%
97272
 
0.6%
85636
 
0.5%
55276
 
0.5%
74833
 
0.4%
Other values (2)9255
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII8700359
100.0%

Most frequent character per block

ValueCountFrequency (%)
-983369
 
11.3%
e835498
 
9.6%
a660662
 
7.6%
r559796
 
6.4%
o554086
 
6.4%
t541085
 
6.2%
i517309
 
5.9%
s480340
 
5.5%
n456219
 
5.2%
l374880
 
4.3%
Other values (28)2737115
31.5%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct474415
Distinct (%)100.0%
Missing2
Missing (%)< 0.1%
Memory size3.6 MiB
UPSHIFT
 
1
Planetary Slingshot
 
1
The Hitman Hunted: Warehouse (1v)
 
1
Tersus
 
1
See No Evil (itch)
 
1
Other values (474410)
474410 

Length

Max length201
Median length17
Mean length19.15812105
Min length1

Characters and Unicode

Total characters9088900
Distinct characters4348
Distinct categories24 ?
Distinct scripts25 ?
Distinct blocks48 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474415 ?
Unique (%)100.0%

Sample

1st rowD/Generation HD
2nd rowG Prime Into The Rain
3rd rowLand Sliders
4th rowPixel Gear
5th rowGods and Idols
ValueCountFrequency (%)
UPSHIFT1
 
< 0.1%
Planetary Slingshot1
 
< 0.1%
The Hitman Hunted: Warehouse (1v)1
 
< 0.1%
Tersus1
 
< 0.1%
See No Evil (itch)1
 
< 0.1%
Plastic Pick-up1
 
< 0.1%
Hoax1
 
< 0.1%
[MZ] Formation Control1
 
< 0.1%
Trick & Treat (itch)1
 
< 0.1%
Asemblance Collection1
 
< 0.1%
Other values (474405)474405
> 99.9%
(Missing)2
 
< 0.1%
2021-03-06T17:07:50.828627image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the52948
 
3.6%
34820
 
2.4%
of25325
 
1.7%
itch21663
 
1.5%
game17180
 
1.2%
a12080
 
0.8%
28991
 
0.6%
and7840
 
0.5%
in7549
 
0.5%
space6842
 
0.5%
Other values (193960)1274857
86.7%

Most occurring characters

ValueCountFrequency (%)
995693
 
11.0%
e772039
 
8.5%
a563121
 
6.2%
o503148
 
5.5%
r477362
 
5.3%
i466623
 
5.1%
t427125
 
4.7%
n413550
 
4.6%
s331291
 
3.6%
l319412
 
3.5%
Other values (4338)3819536
42.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6082410
66.9%
Uppercase Letter1512685
 
16.6%
Space Separator995722
 
11.0%
Decimal Number123239
 
1.4%
Other Punctuation120868
 
1.3%
Close Punctuation79323
 
0.9%
Open Punctuation79315
 
0.9%
Dash Punctuation43753
 
0.5%
Other Letter39455
 
0.4%
Connector Punctuation4514
 
< 0.1%
Other values (14)7616
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
ا1387
 
3.5%
ل918
 
2.3%
ب496
 
1.3%
ي397
 
1.0%
ر391
 
1.0%
ع352
 
0.9%
و345
 
0.9%
م342
 
0.9%
340
 
0.9%
338
 
0.9%
Other values (3299)34149
86.6%
ValueCountFrequency (%)
e772039
12.7%
a563121
 
9.3%
o503148
 
8.3%
r477362
 
7.8%
i466623
 
7.7%
t427125
 
7.0%
n413550
 
6.8%
s331291
 
5.4%
l319412
 
5.3%
h216022
 
3.6%
Other values (293)1592717
26.2%
ValueCountFrequency (%)
S150549
 
10.0%
T118125
 
7.8%
C103183
 
6.8%
D96031
 
6.3%
A92608
 
6.1%
R86101
 
5.7%
B85966
 
5.7%
P84143
 
5.6%
M81453
 
5.4%
G69409
 
4.6%
Other values (165)545117
36.0%
ValueCountFrequency (%)
595
47.3%
°65
 
5.2%
43
 
3.4%
35
 
2.8%
33
 
2.6%
©32
 
2.5%
¦29
 
2.3%
28
 
2.2%
24
 
1.9%
23
 
1.8%
Other values (137)352
28.0%
ValueCountFrequency (%)
35
 
7.2%
̶32
 
6.6%
30
 
6.2%
͡15
 
3.1%
̷15
 
3.1%
13
 
2.7%
̴12
 
2.5%
12
 
2.5%
12
 
2.5%
11
 
2.3%
Other values (108)296
61.3%
ValueCountFrequency (%)
:38752
32.1%
'21662
17.9%
.19787
16.4%
!17678
14.6%
,8436
 
7.0%
&5257
 
4.3%
?2538
 
2.1%
/2300
 
1.9%
#1160
 
1.0%
"1152
 
1.0%
Other values (49)2146
 
1.8%
ValueCountFrequency (%)
+1219
37.9%
|739
23.0%
~512
15.9%
179
 
5.6%
>119
 
3.7%
<110
 
3.4%
=109
 
3.4%
41
 
1.3%
27
 
0.8%
23
 
0.7%
Other values (36)136
 
4.2%
ValueCountFrequency (%)
549
82.3%
ˆ17
 
2.5%
ـ14
 
2.1%
ʻ12
 
1.8%
8
 
1.2%
7
 
1.0%
5
 
0.7%
4
 
0.6%
4
 
0.6%
4
 
0.6%
Other values (29)43
 
6.4%
ValueCountFrequency (%)
227084
22.0%
023013
18.7%
121725
17.6%
315493
12.6%
48709
 
7.1%
97244
 
5.9%
85582
 
4.5%
55048
 
4.1%
74643
 
3.8%
64632
 
3.8%
Other values (20)66
 
0.1%
ValueCountFrequency (%)
™4
12.9%
€3
9.7%
‹3
9.7%
‚3
9.7%
ƒ3
9.7%
Ž2
 
6.5%
‰2
 
6.5%
2
 
6.5%
œ2
 
6.5%
Œ2
 
6.5%
Other values (5)5
16.1%
ValueCountFrequency (%)
(76482
96.4%
[2515
 
3.2%
104
 
0.1%
{76
 
0.1%
39
 
< 0.1%
29
 
< 0.1%
24
 
< 0.1%
16
 
< 0.1%
13
 
< 0.1%
13
 
< 0.1%
Other values (4)4
 
< 0.1%
ValueCountFrequency (%)
)76543
96.5%
]2514
 
3.2%
104
 
0.1%
}75
 
0.1%
39
 
< 0.1%
16
 
< 0.1%
13
 
< 0.1%
13
 
< 0.1%
1
 
< 0.1%
1
 
< 0.1%
Other values (4)4
 
< 0.1%
ValueCountFrequency (%)
²70
38.9%
³28
 
15.6%
½24
 
13.3%
¹22
 
12.2%
¾12
 
6.7%
¼12
 
6.7%
4
 
2.2%
2
 
1.1%
2
 
1.1%
1
 
0.6%
Other values (3)3
 
1.7%
ValueCountFrequency (%)
$111
37.2%
86
28.9%
¥35
 
11.7%
¤25
 
8.4%
£19
 
6.4%
¢15
 
5.0%
2
 
0.7%
2
 
0.7%
1
 
0.3%
1
 
0.3%
ValueCountFrequency (%)
-42674
97.5%
677
 
1.5%
263
 
0.6%
65
 
0.1%
50
 
0.1%
11
 
< 0.1%
7
 
< 0.1%
5
 
< 0.1%
1
 
< 0.1%
ValueCountFrequency (%)
´163
31.5%
`118
22.8%
^88
17.0%
¸64
 
12.4%
˜49
 
9.5%
¨20
 
3.9%
¯13
 
2.5%
2
 
0.4%
1
 
0.2%
ValueCountFrequency (%)
72
54.5%
­25
 
18.9%
14
 
10.6%
8
 
6.1%
8
 
6.1%
3
 
2.3%
1
 
0.8%
؜1
 
0.8%
ValueCountFrequency (%)
20
39.2%
12
23.5%
8
 
15.7%
5
 
9.8%
3
 
5.9%
2
 
3.9%
1
 
2.0%
ValueCountFrequency (%)
3
27.3%
2
18.2%
2
18.2%
1
 
9.1%
1
 
9.1%
ि1
 
9.1%
1
 
9.1%
ValueCountFrequency (%)
470
79.1%
74
 
12.5%
»32
 
5.4%
18
 
3.0%
ValueCountFrequency (%)
83
47.7%
54
31.0%
20
 
11.5%
«17
 
9.8%
ValueCountFrequency (%)
995693
> 99.9%
 28
 
< 0.1%
 1
 
< 0.1%
ValueCountFrequency (%)
_4511
99.9%
3
 
0.1%
ValueCountFrequency (%)
҉3
75.0%
1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7574708
83.3%
Common1453724
 
16.0%
Han20747
 
0.2%
Cyrillic19516
 
0.2%
Arabic7402
 
0.1%
Katakana5071
 
0.1%
Hiragana3242
 
< 0.1%
Hangul2102
 
< 0.1%
Greek878
 
< 0.1%
Thai564
 
< 0.1%
Other values (15)946
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
312
 
1.5%
311
 
1.5%
258
 
1.2%
257
 
1.2%
197
 
0.9%
196
 
0.9%
169
 
0.8%
158
 
0.8%
148
 
0.7%
144
 
0.7%
Other values (2477)18597
89.6%
ValueCountFrequency (%)
48
 
2.3%
46
 
2.2%
43
 
2.0%
42
 
2.0%
38
 
1.8%
35
 
1.7%
27
 
1.3%
26
 
1.2%
24
 
1.1%
23
 
1.1%
Other values (446)1750
83.3%
ValueCountFrequency (%)
995693
68.5%
)76543
 
5.3%
(76482
 
5.3%
-42674
 
2.9%
:38752
 
2.7%
227084
 
1.9%
023013
 
1.6%
121725
 
1.5%
'21662
 
1.5%
.19787
 
1.4%
Other values (363)110309
 
7.6%
ValueCountFrequency (%)
e772039
 
10.2%
a563121
 
7.4%
o503148
 
6.6%
r477362
 
6.3%
i466623
 
6.2%
t427125
 
5.6%
n413550
 
5.5%
s331291
 
4.4%
l319412
 
4.2%
h216022
 
2.9%
Other values (326)3085015
40.7%
ValueCountFrequency (%)
338
 
6.7%
225
 
4.4%
221
 
4.4%
183
 
3.6%
179
 
3.5%
172
 
3.4%
165
 
3.3%
158
 
3.1%
151
 
3.0%
148
 
2.9%
Other values (94)3131
61.7%
ValueCountFrequency (%)
̶32
 
8.9%
30
 
8.3%
͡15
 
4.2%
̷15
 
4.2%
̴12
 
3.3%
͈10
 
2.8%
̨9
 
2.5%
̸8
 
2.2%
̵7
 
1.9%
̞7
 
1.9%
Other values (83)215
59.7%
ValueCountFrequency (%)
340
 
10.5%
192
 
5.9%
139
 
4.3%
111
 
3.4%
110
 
3.4%
103
 
3.2%
99
 
3.1%
96
 
3.0%
91
 
2.8%
91
 
2.8%
Other values (68)1870
57.7%
ValueCountFrequency (%)
о1692
 
8.7%
а1673
 
8.6%
и1477
 
7.6%
е1424
 
7.3%
р1134
 
5.8%
н1128
 
5.8%
т952
 
4.9%
к859
 
4.4%
с801
 
4.1%
л746
 
3.8%
Other values (67)7630
39.1%
ValueCountFrequency (%)
ο68
 
7.7%
α56
 
6.4%
ε54
 
6.2%
τ51
 
5.8%
ι51
 
5.8%
ρ47
 
5.4%
ς42
 
4.8%
λ31
 
3.5%
ν29
 
3.3%
π26
 
3.0%
Other values (52)423
48.2%
ValueCountFrequency (%)
63
 
11.2%
35
 
6.2%
27
 
4.8%
27
 
4.8%
24
 
4.3%
23
 
4.1%
21
 
3.7%
21
 
3.7%
20
 
3.5%
15
 
2.7%
Other values (45)288
51.1%
ValueCountFrequency (%)
ا1387
18.7%
ل918
12.4%
ب496
 
6.7%
ي397
 
5.4%
ر391
 
5.3%
ع352
 
4.8%
و345
 
4.7%
م342
 
4.6%
ن324
 
4.4%
ت320
 
4.3%
Other values (37)2130
28.8%
ValueCountFrequency (%)
ו31
 
10.0%
י31
 
10.0%
ה29
 
9.3%
ש20
 
6.4%
ב20
 
6.4%
א18
 
5.8%
ר17
 
5.5%
ל17
 
5.5%
ח16
 
5.1%
מ16
 
5.1%
Other values (17)96
30.9%
ValueCountFrequency (%)
3
 
8.6%
3
 
8.6%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (17)17
48.6%
ValueCountFrequency (%)
20
19.6%
10
9.8%
10
9.8%
10
9.8%
9
8.8%
5
 
4.9%
5
 
4.9%
5
 
4.9%
4
 
3.9%
4
 
3.9%
Other values (11)20
19.6%
ValueCountFrequency (%)
3
 
10.0%
3
 
10.0%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
1
 
3.3%
1
 
3.3%
Other values (10)10
33.3%
ValueCountFrequency (%)
ߤ3
 
13.0%
߄2
 
8.7%
ߵ1
 
4.3%
ߍ1
 
4.3%
ߦ1
 
4.3%
ߗ1
 
4.3%
߭1
 
4.3%
߆1
 
4.3%
ߓ1
 
4.3%
߫1
 
4.3%
Other values (10)10
43.5%
ValueCountFrequency (%)
ա3
21.4%
լ1
 
7.1%
վ1
 
7.1%
շ1
 
7.1%
։1
 
7.1%
Ե1
 
7.1%
ս1
 
7.1%
գ1
 
7.1%
ի1
 
7.1%
տ1
 
7.1%
Other values (2)2
14.3%
ValueCountFrequency (%)
6
35.3%
3
17.6%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
ValueCountFrequency (%)
2
16.7%
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
ValueCountFrequency (%)
4
28.6%
2
14.3%
2
14.3%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
ValueCountFrequency (%)
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
ి1
12.5%
1
12.5%
1
12.5%
1
12.5%
ValueCountFrequency (%)
2
28.6%
2
28.6%
1
14.3%
1
14.3%
1
14.3%
ValueCountFrequency (%)
1
50.0%
1
50.0%
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9013909
99.2%
CJK20737
 
0.2%
Cyrillic19516
 
0.2%
None11016
 
0.1%
Arabic7436
 
0.1%
Katakana5643
 
0.1%
Hiragana3245
 
< 0.1%
Punctuation2105
 
< 0.1%
Hangul2096
 
< 0.1%
Specials595
 
< 0.1%
Other values (38)2602
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
995693
 
11.0%
e772039
 
8.6%
a563121
 
6.2%
o503148
 
5.6%
r477362
 
5.3%
i466623
 
5.2%
t427125
 
4.7%
n413550
 
4.6%
s331291
 
3.7%
l319412
 
3.5%
Other values (85)3744545
41.5%
ValueCountFrequency (%)
é1144
 
10.4%
ğ510
 
4.6%
Ÿ484
 
4.4%
á393
 
3.6%
ó368
 
3.3%
í331
 
3.0%
ã324
 
2.9%
ç295
 
2.7%
ð200
 
1.8%
ö196
 
1.8%
Other values (388)6771
61.5%
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
ValueCountFrequency (%)
677
32.2%
470
22.3%
263
 
12.5%
145
 
6.9%
83
 
3.9%
74
 
3.5%
72
 
3.4%
54
 
2.6%
42
 
2.0%
38
 
1.8%
Other values (24)187
 
8.9%
ValueCountFrequency (%)
28
20.7%
15
11.1%
11
 
8.1%
11
 
8.1%
10
 
7.4%
10
 
7.4%
5
 
3.7%
5
 
3.7%
4
 
3.0%
4
 
3.0%
Other values (20)32
23.7%
ValueCountFrequency (%)
41
31.1%
27
20.5%
23
17.4%
5
 
3.8%
5
 
3.8%
4
 
3.0%
4
 
3.0%
4
 
3.0%
3
 
2.3%
2
 
1.5%
Other values (12)14
 
10.6%
ValueCountFrequency (%)
4
50.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%
1
 
12.5%
ValueCountFrequency (%)
312
 
1.5%
311
 
1.5%
258
 
1.2%
257
 
1.2%
197
 
0.9%
196
 
0.9%
169
 
0.8%
158
 
0.8%
148
 
0.7%
144
 
0.7%
Other values (2475)18587
89.6%
ValueCountFrequency (%)
549
 
9.7%
338
 
6.0%
225
 
4.0%
221
 
3.9%
183
 
3.2%
179
 
3.2%
172
 
3.0%
165
 
2.9%
158
 
2.8%
151
 
2.7%
Other values (76)3302
58.5%
ValueCountFrequency (%)
35
21.5%
24
14.7%
14
 
8.6%
7
 
4.3%
5
 
3.1%
5
 
3.1%
4
 
2.5%
4
 
2.5%
3
 
1.8%
3
 
1.8%
Other values (37)59
36.2%
ValueCountFrequency (%)
̶32
 
10.3%
͡15
 
4.8%
̷15
 
4.8%
̴12
 
3.8%
͈10
 
3.2%
̨9
 
2.9%
̸8
 
2.6%
̵7
 
2.2%
̞7
 
2.2%
̀6
 
1.9%
Other values (75)191
61.2%
ValueCountFrequency (%)
340
 
10.5%
192
 
5.9%
139
 
4.3%
111
 
3.4%
110
 
3.4%
103
 
3.2%
99
 
3.1%
96
 
3.0%
91
 
2.8%
91
 
2.8%
Other values (71)1873
57.7%
ValueCountFrequency (%)
23
30.3%
8
 
10.5%
7
 
9.2%
7
 
9.2%
6
 
7.9%
4
 
5.3%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
Other values (10)11
14.5%
ValueCountFrequency (%)
30
83.3%
6
 
16.7%
ValueCountFrequency (%)
ا1387
18.7%
ل918
12.3%
ب496
 
6.7%
ي397
 
5.3%
ر391
 
5.3%
ع352
 
4.7%
و345
 
4.6%
م342
 
4.6%
ن324
 
4.4%
ت320
 
4.3%
Other values (43)2164
29.1%
ValueCountFrequency (%)
о1692
 
8.7%
а1673
 
8.6%
и1477
 
7.6%
е1424
 
7.3%
р1134
 
5.8%
н1128
 
5.8%
т952
 
4.9%
к859
 
4.4%
с801
 
4.1%
л746
 
3.8%
Other values (67)7630
39.1%
ValueCountFrequency (%)
48
 
2.3%
46
 
2.2%
43
 
2.1%
42
 
2.0%
38
 
1.8%
35
 
1.7%
27
 
1.3%
26
 
1.2%
24
 
1.1%
23
 
1.1%
Other values (442)1744
83.2%
ValueCountFrequency (%)
595
100.0%
ValueCountFrequency (%)
33
73.3%
5
 
11.1%
3
 
6.7%
2
 
4.4%
1
 
2.2%
1
 
2.2%
ValueCountFrequency (%)
ế18
16.2%
8
 
7.2%
7
 
6.3%
7
 
6.3%
6
 
5.4%
6
 
5.4%
5
 
4.5%
4
 
3.6%
4
 
3.6%
4
 
3.6%
Other values (22)42
37.8%
ValueCountFrequency (%)
86
92.5%
2
 
2.2%
2
 
2.2%
1
 
1.1%
1
 
1.1%
1
 
1.1%
ValueCountFrequency (%)
4
28.6%
2
14.3%
2
14.3%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
ValueCountFrequency (%)
ו31
 
10.0%
י31
 
10.0%
ה29
 
9.4%
ש20
 
6.5%
ב20
 
6.5%
א18
 
5.8%
ר17
 
5.5%
ל17
 
5.5%
ח16
 
5.2%
מ16
 
5.2%
Other values (16)95
30.6%
ValueCountFrequency (%)
5
23.8%
5
23.8%
3
14.3%
3
14.3%
2
 
9.5%
1
 
4.8%
1
 
4.8%
1
 
4.8%
ValueCountFrequency (%)
˜49
52.7%
ˆ17
 
18.3%
ʻ12
 
12.9%
ˈ3
 
3.2%
ˌ2
 
2.2%
ʰ2
 
2.2%
ʳ2
 
2.2%
ˡ2
 
2.2%
ː1
 
1.1%
ˢ1
 
1.1%
Other values (2)2
 
2.2%
ValueCountFrequency (%)
63
 
11.2%
35
 
6.2%
27
 
4.8%
27
 
4.8%
24
 
4.3%
23
 
4.1%
21
 
3.7%
21
 
3.7%
20
 
3.5%
15
 
2.7%
Other values (45)288
51.1%
ValueCountFrequency (%)
20
45.5%
12
27.3%
5
 
11.4%
3
 
6.8%
2
 
4.5%
1
 
2.3%
1
 
2.3%
ValueCountFrequency (%)
6
35.3%
3
17.6%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
ValueCountFrequency (%)
43
78.2%
5
 
9.1%
2
 
3.6%
2
 
3.6%
1
 
1.8%
1
 
1.8%
1
 
1.8%
ValueCountFrequency (%)
ʀ6
12.8%
ɹ5
 
10.6%
ʇ4
 
8.5%
ɯ3
 
6.4%
ɪ3
 
6.4%
ə3
 
6.4%
ʖ3
 
6.4%
ʙ3
 
6.4%
ʟ2
 
4.3%
ɟ2
 
4.3%
Other values (12)13
27.7%
ValueCountFrequency (%)
ա3
21.4%
լ1
 
7.1%
վ1
 
7.1%
շ1
 
7.1%
։1
 
7.1%
Ե1
 
7.1%
ս1
 
7.1%
գ1
 
7.1%
ի1
 
7.1%
տ1
 
7.1%
Other values (2)2
14.3%
ValueCountFrequency (%)
3
 
8.6%
3
 
8.6%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (17)17
48.6%
ValueCountFrequency (%)
5
11.1%
5
11.1%
4
 
8.9%
4
 
8.9%
4
 
8.9%
3
 
6.7%
3
 
6.7%
3
 
6.7%
2
 
4.4%
2
 
4.4%
Other values (9)10
22.2%
ValueCountFrequency (%)
20
19.6%
10
9.8%
10
9.8%
10
9.8%
9
8.8%
5
 
4.9%
5
 
4.9%
5
 
4.9%
4
 
3.9%
4
 
3.9%
Other values (11)20
19.6%
ValueCountFrequency (%)
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
ValueCountFrequency (%)
2
25.0%
2
25.0%
2
25.0%
2
25.0%
ValueCountFrequency (%)
3
 
9.7%
3
 
9.7%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
1
 
3.2%
Other values (11)11
35.5%
ValueCountFrequency (%)
2
22.2%
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
8
88.9%
1
 
11.1%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
ߤ3
 
13.0%
߄2
 
8.7%
ߵ1
 
4.3%
ߍ1
 
4.3%
ߦ1
 
4.3%
ߗ1
 
4.3%
߭1
 
4.3%
߆1
 
4.3%
ߓ1
 
4.3%
߫1
 
4.3%
Other values (10)10
43.5%
ValueCountFrequency (%)
2
50.0%
2
50.0%
ValueCountFrequency (%)
1
50.0%
1
50.0%
ValueCountFrequency (%)
2
28.6%
2
28.6%
1
14.3%
1
14.3%
1
14.3%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
2
15.4%
2
15.4%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
ి1
12.5%
1
12.5%
1
12.5%
1
12.5%

metacritic
Real number (ℝ≥0)

MISSING

Distinct78
Distinct (%)1.6%
Missing469684
Missing (%)99.0%
Infinite0
Infinite (%)0.0%
Mean73.15930699
Minimum15
Maximum99
Zeros0
Zeros (%)0.0%
Memory size3.6 MiB
2021-03-06T17:07:51.051261image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile52
Q167
median75
Q381
95-th percentile90
Maximum99
Range84
Interquartile range (IQR)14

Descriptive statistics

Standard deviation11.50221305
Coefficient of variation (CV)0.1572214599
Kurtosis1.070188556
Mean73.15930699
Median Absolute Deviation (MAD)7
Skewness-0.8182856206
Sum346263
Variance132.300905
MonotocityNot monotonic
2021-03-06T17:07:51.190949image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80233
 
< 0.1%
78188
 
< 0.1%
76185
 
< 0.1%
74183
 
< 0.1%
75180
 
< 0.1%
81180
 
< 0.1%
72172
 
< 0.1%
77169
 
< 0.1%
73162
 
< 0.1%
68152
 
< 0.1%
Other values (68)2929
 
0.6%
(Missing)469684
99.0%
ValueCountFrequency (%)
151
< 0.1%
201
< 0.1%
221
< 0.1%
241
< 0.1%
252
< 0.1%
ValueCountFrequency (%)
991
 
< 0.1%
982
 
< 0.1%
977
< 0.1%
969
< 0.1%
9513
< 0.1%

released
Categorical

HIGH CARDINALITY
MISSING

Distinct8631
Distinct (%)1.9%
Missing24199
Missing (%)5.1%
Memory size3.6 MiB
2020-07-12
 
4839
2019-08-04
 
2311
2020-04-20
 
1862
2020-10-05
 
1820
2020-04-21
 
1458
Other values (8626)
437928 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4502180
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1922 ?
Unique (%)0.4%

Sample

1st row2015-10-23
2nd row2016-01-06
3rd row2015-09-24
4th row2016-10-20
5th row2016-12-12
ValueCountFrequency (%)
2020-07-124839
 
1.0%
2019-08-042311
 
0.5%
2020-04-201862
 
0.4%
2020-10-051820
 
0.4%
2020-04-211458
 
0.3%
2020-08-081335
 
0.3%
2019-10-071156
 
0.2%
2018-08-131055
 
0.2%
2018-09-021044
 
0.2%
2020-11-151016
 
0.2%
Other values (8621)432322
91.1%
(Missing)24199
 
5.1%
2021-03-06T17:07:51.491160image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-07-124839
 
1.1%
2019-08-042311
 
0.5%
2020-04-201862
 
0.4%
2020-10-051820
 
0.4%
2020-04-211458
 
0.3%
2020-08-081335
 
0.3%
2019-10-071156
 
0.3%
2018-08-131055
 
0.2%
2018-09-021044
 
0.2%
2020-11-151016
 
0.2%
Other values (8621)432322
96.0%

Most occurring characters

ValueCountFrequency (%)
01138614
25.3%
-900436
20.0%
2820313
18.2%
1719200
16.0%
9176839
 
3.9%
8163302
 
3.6%
7140491
 
3.1%
6117834
 
2.6%
3110791
 
2.5%
5108852
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3601744
80.0%
Dash Punctuation900436
 
20.0%

Most frequent character per category

ValueCountFrequency (%)
01138614
31.6%
2820313
22.8%
1719200
20.0%
9176839
 
4.9%
8163302
 
4.5%
7140491
 
3.9%
6117834
 
3.3%
3110791
 
3.1%
5108852
 
3.0%
4105508
 
2.9%
ValueCountFrequency (%)
-900436
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common4502180
100.0%

Most frequent character per script

ValueCountFrequency (%)
01138614
25.3%
-900436
20.0%
2820313
18.2%
1719200
16.0%
9176839
 
3.9%
8163302
 
3.6%
7140491
 
3.1%
6117834
 
2.6%
3110791
 
2.5%
5108852
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII4502180
100.0%

Most frequent character per block

ValueCountFrequency (%)
01138614
25.3%
-900436
20.0%
2820313
18.2%
1719200
16.0%
9176839
 
3.9%
8163302
 
3.6%
7140491
 
3.1%
6117834
 
2.6%
3110791
 
2.5%
5108852
 
2.4%

tba
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size463.4 KiB
False
472076 
True
 
2341
ValueCountFrequency (%)
False472076
99.5%
True2341
 
0.5%
2021-03-06T17:07:51.566924image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

updated
Categorical

HIGH CARDINALITY

Distinct241644
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
2019-01-09T12:41:06
139894 
2019-08-23T11:27:41
 
43
2019-08-28T23:14:41
 
39
2019-08-28T23:14:37
 
38
2019-08-28T23:14:43
 
38
Other values (241639)
334365 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters9013923
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique230501 ?
Unique (%)48.6%

Sample

1st row2019-09-17T11:58:57
2nd row2019-11-06T23:04:19
3rd row2019-10-22T13:56:16
4th row2019-08-28T22:16:02
5th row2019-09-17T13:37:13
ValueCountFrequency (%)
2019-01-09T12:41:06139894
29.5%
2019-08-23T11:27:4143
 
< 0.1%
2019-08-28T23:14:4139
 
< 0.1%
2019-08-28T23:14:3738
 
< 0.1%
2019-08-28T23:14:4338
 
< 0.1%
2019-08-28T23:14:3237
 
< 0.1%
2019-09-12T06:39:3237
 
< 0.1%
2019-08-28T23:14:3537
 
< 0.1%
2019-08-28T23:24:1637
 
< 0.1%
2019-10-22T14:19:3836
 
< 0.1%
Other values (241634)334181
70.4%
2021-03-06T17:07:52.628217image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-01-09t12:41:06139894
29.5%
2019-08-23t11:27:4143
 
< 0.1%
2019-08-28t23:14:4139
 
< 0.1%
2019-08-28t23:14:4338
 
< 0.1%
2019-08-28t23:14:3738
 
< 0.1%
2019-08-28t23:24:1637
 
< 0.1%
2019-09-12t06:39:3237
 
< 0.1%
2019-08-28t23:14:3237
 
< 0.1%
2019-08-28t23:14:3537
 
< 0.1%
2019-10-22t14:19:3836
 
< 0.1%
Other values (241634)334181
70.4%

Most occurring characters

ValueCountFrequency (%)
01812016
20.1%
21291826
14.3%
11288863
14.3%
-948834
10.5%
:948834
10.5%
9616794
 
6.8%
T474417
 
5.3%
4433904
 
4.8%
3306262
 
3.4%
6277991
 
3.1%
Other values (3)614182
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6641838
73.7%
Dash Punctuation948834
 
10.5%
Other Punctuation948834
 
10.5%
Uppercase Letter474417
 
5.3%

Most frequent character per category

ValueCountFrequency (%)
01812016
27.3%
21291826
19.4%
11288863
19.4%
9616794
 
9.3%
4433904
 
6.5%
3306262
 
4.6%
6277991
 
4.2%
5245506
 
3.7%
8218307
 
3.3%
7150369
 
2.3%
ValueCountFrequency (%)
-948834
100.0%
ValueCountFrequency (%)
T474417
100.0%
ValueCountFrequency (%)
:948834
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common8539506
94.7%
Latin474417
 
5.3%

Most frequent character per script

ValueCountFrequency (%)
01812016
21.2%
21291826
15.1%
11288863
15.1%
-948834
11.1%
:948834
11.1%
9616794
 
7.2%
4433904
 
5.1%
3306262
 
3.6%
6277991
 
3.3%
5245506
 
2.9%
Other values (2)368676
 
4.3%
ValueCountFrequency (%)
T474417
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9013923
100.0%

Most frequent character per block

ValueCountFrequency (%)
01812016
20.1%
21291826
14.3%
11288863
14.3%
-948834
10.5%
:948834
10.5%
9616794
 
6.8%
T474417
 
5.3%
4433904
 
4.8%
3306262
 
3.4%
6277991
 
3.1%
Other values (3)614182
 
6.8%

website
Categorical

HIGH CARDINALITY
MISSING

Distinct46969
Distinct (%)72.2%
Missing409376
Missing (%)86.3%
Memory size3.6 MiB
http://www.bigfishgames.com/mobile-games/ios-games/
 
166
https://www.choiceofgames.com/
 
151
http://
 
106
https://www.facebook.com/8FloorGames/
 
91
http://www.gameloft.com
 
80
Other values (46964)
64447 

Length

Max length496
Median length29
Mean length33.38724804
Min length7

Characters and Unicode

Total characters2171540
Distinct characters115
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41650 ?
Unique (%)64.0%

Sample

1st rowhttp://dgeneration.net
2nd rowhttp://prettygreat.com
3rd rowhttps://www.facebook.com/Geronimo-Interactive-1789605664633280/?ref=bookmarks
4th rowhttp://www.godsandidols.com/
5th rowhttp://www.croteam.com
ValueCountFrequency (%)
http://www.bigfishgames.com/mobile-games/ios-games/166
 
< 0.1%
https://www.choiceofgames.com/151
 
< 0.1%
http://106
 
< 0.1%
https://www.facebook.com/8FloorGames/91
 
< 0.1%
http://www.gameloft.com80
 
< 0.1%
http://www.g5e.com79
 
< 0.1%
http://www.propheticdevelopers.com75
 
< 0.1%
http://www.sega.com69
 
< 0.1%
http://smartkids-games.com66
 
< 0.1%
http://gruv-apps.com62
 
< 0.1%
Other values (46959)64096
 
13.5%
(Missing)409376
86.3%
2021-03-06T17:07:53.024334image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
http://www.bigfishgames.com/mobile-games/ios-games167
 
0.3%
https://www.choiceofgames.com158
 
0.2%
https://www.facebook.com/8floorgames111
 
0.2%
http107
 
0.2%
http://www.gameloft.com88
 
0.1%
http://www.propheticdevelopers.com86
 
0.1%
http://www.g5e.com79
 
0.1%
http://www.sega.com71
 
0.1%
http://smartkids-games.com67
 
0.1%
http://www.mokoolapps.com63
 
0.1%
Other values (45907)64054
98.5%

Most occurring characters

ValueCountFrequency (%)
t204449
 
9.4%
/194466
 
9.0%
o139601
 
6.4%
w129187
 
5.9%
e127676
 
5.9%
.118873
 
5.5%
m110768
 
5.1%
a109391
 
5.0%
p104198
 
4.8%
h95530
 
4.4%
Other values (105)837401
38.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1697505
78.2%
Other Punctuation383477
 
17.7%
Decimal Number40047
 
1.8%
Dash Punctuation23456
 
1.1%
Uppercase Letter19802
 
0.9%
Connector Punctuation3740
 
0.2%
Math Symbol3478
 
0.2%
Space Separator17
 
< 0.1%
Open Punctuation5
 
< 0.1%
Close Punctuation5
 
< 0.1%
Other values (5)8
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
t204449
12.0%
o139601
 
8.2%
w129187
 
7.6%
e127676
 
7.5%
m110768
 
6.5%
a109391
 
6.4%
p104198
 
6.1%
h95530
 
5.6%
s94771
 
5.6%
c94435
 
5.6%
Other values (36)487499
28.7%
ValueCountFrequency (%)
G1842
 
9.3%
S1611
 
8.1%
P1364
 
6.9%
A1362
 
6.9%
C1206
 
6.1%
D1160
 
5.9%
T1005
 
5.1%
F932
 
4.7%
M929
 
4.7%
B881
 
4.4%
Other values (19)7510
37.9%
ValueCountFrequency (%)
/194466
50.7%
.118873
31.0%
:65225
 
17.0%
?2472
 
0.6%
&1153
 
0.3%
%700
 
0.2%
#307
 
0.1%
;166
 
< 0.1%
!82
 
< 0.1%
,13
 
< 0.1%
Other values (3)20
 
< 0.1%
ValueCountFrequency (%)
26349
15.9%
15903
14.7%
04931
12.3%
34180
10.4%
53538
8.8%
43351
8.4%
83130
7.8%
73118
7.8%
62893
7.2%
92654
6.6%
ValueCountFrequency (%)
=3363
96.7%
+49
 
1.4%
~35
 
1.0%
|31
 
0.9%
ValueCountFrequency (%)
鸿1
25.0%
1
25.0%
1
25.0%
1
25.0%
ValueCountFrequency (%)
-23456
100.0%
ValueCountFrequency (%)
_3740
100.0%
ValueCountFrequency (%)
17
100.0%
ValueCountFrequency (%)
©1
100.0%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
²1
100.0%
ValueCountFrequency (%)
[5
100.0%
ValueCountFrequency (%)
]5
100.0%
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1717266
79.1%
Common454229
 
20.9%
Cyrillic41
 
< 0.1%
Han4
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
t204449
11.9%
o139601
 
8.1%
w129187
 
7.5%
e127676
 
7.4%
m110768
 
6.5%
a109391
 
6.4%
p104198
 
6.1%
h95530
 
5.6%
s94771
 
5.5%
c94435
 
5.5%
Other values (47)507260
29.5%
ValueCountFrequency (%)
/194466
42.8%
.118873
26.2%
:65225
 
14.4%
-23456
 
5.2%
26349
 
1.4%
15903
 
1.3%
04931
 
1.1%
34180
 
0.9%
_3740
 
0.8%
53538
 
0.8%
Other values (26)23568
 
5.2%
ValueCountFrequency (%)
о6
14.6%
р4
9.8%
т4
9.8%
е4
9.8%
я3
 
7.3%
и3
 
7.3%
к2
 
4.9%
л2
 
4.9%
с2
 
4.9%
в2
 
4.9%
Other values (8)9
22.0%
ValueCountFrequency (%)
鸿1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2171484
> 99.9%
Cyrillic41
 
< 0.1%
None10
 
< 0.1%
CJK4
 
< 0.1%
Punctuation1
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
t204449
 
9.4%
/194466
 
9.0%
o139601
 
6.4%
w129187
 
5.9%
e127676
 
5.9%
.118873
 
5.5%
m110768
 
5.1%
a109391
 
5.0%
p104198
 
4.8%
h95530
 
4.4%
Other values (75)837345
38.6%
ValueCountFrequency (%)
ä2
20.0%
ð2
20.0%
Ÿ2
20.0%
š1
10.0%
©1
10.0%
²1
10.0%
á1
10.0%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
о6
14.6%
р4
9.8%
т4
9.8%
е4
9.8%
я3
 
7.3%
и3
 
7.3%
к2
 
4.9%
л2
 
4.9%
с2
 
4.9%
в2
 
4.9%
Other values (8)9
22.0%
ValueCountFrequency (%)
鸿1
25.0%
1
25.0%
1
25.0%
1
25.0%

rating
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct351
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0857232772
Minimum0
Maximum5
Zeros462423
Zeros (%)97.5%
Memory size3.6 MiB
2021-03-06T17:07:53.166281image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5450488518
Coefficient of variation (CV)6.358236287
Kurtosis40.62924235
Mean0.0857232772
Median Absolute Deviation (MAD)0
Skewness6.43406525
Sum40668.58
Variance0.2970782508
MonotocityNot monotonic
2021-03-06T17:07:53.305428image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0462423
97.5%
4412
 
0.1%
3293
 
0.1%
3.5201
 
< 0.1%
3.67191
 
< 0.1%
3.33171
 
< 0.1%
4.33137
 
< 0.1%
3.83136
 
< 0.1%
2133
 
< 0.1%
3.71126
 
< 0.1%
Other values (341)10194
 
2.1%
ValueCountFrequency (%)
0462423
97.5%
16
 
< 0.1%
1.111
 
< 0.1%
1.131
 
< 0.1%
1.171
 
< 0.1%
ValueCountFrequency (%)
51
 
< 0.1%
4.861
 
< 0.1%
4.833
< 0.1%
4.811
 
< 0.1%
4.781
 
< 0.1%

rating_top
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
0
461178 
4
 
7113
3
 
2716
5
 
1719
1
 
1691

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters474417
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1
ValueCountFrequency (%)
0461178
97.2%
47113
 
1.5%
32716
 
0.6%
51719
 
0.4%
11691
 
0.4%
2021-03-06T17:07:53.535288image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-03-06T17:07:53.603608image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
0461178
97.2%
47113
 
1.5%
32716
 
0.6%
51719
 
0.4%
11691
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0461178
97.2%
47113
 
1.5%
32716
 
0.6%
51719
 
0.4%
11691
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number474417
100.0%

Most frequent character per category

ValueCountFrequency (%)
0461178
97.2%
47113
 
1.5%
32716
 
0.6%
51719
 
0.4%
11691
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common474417
100.0%

Most frequent character per script

ValueCountFrequency (%)
0461178
97.2%
47113
 
1.5%
32716
 
0.6%
51719
 
0.4%
11691
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII474417
100.0%

Most frequent character per block

ValueCountFrequency (%)
0461178
97.2%
47113
 
1.5%
32716
 
0.6%
51719
 
0.4%
11691
 
0.4%

playtime
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct137
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2216615341
Minimum0
Maximum1600
Zeros451355
Zeros (%)95.1%
Memory size3.6 MiB
2021-03-06T17:07:53.705551image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1600
Range1600
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.399684108
Coefficient of variation (CV)24.36004123
Kurtosis42394.1729
Mean0.2216615341
Median Absolute Deviation (MAD)0
Skewness181.4873355
Sum105160
Variance29.15658846
MonotocityNot monotonic
2021-03-06T17:07:53.832288image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0451355
95.1%
18939
 
1.9%
43442
 
0.7%
33107
 
0.7%
22980
 
0.6%
51655
 
0.3%
6763
 
0.2%
7395
 
0.1%
8259
 
0.1%
9208
 
< 0.1%
Other values (127)1314
 
0.3%
ValueCountFrequency (%)
0451355
95.1%
18939
 
1.9%
22980
 
0.6%
33107
 
0.7%
43442
 
0.7%
ValueCountFrequency (%)
16001
< 0.1%
14731
< 0.1%
12461
< 0.1%
10461
< 0.1%
9001
< 0.1%

achievements_count
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct556
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.448837204
Minimum0
Maximum12322
Zeros456734
Zeros (%)96.3%
Memory size3.6 MiB
2021-03-06T17:07:53.963862image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum12322
Range12322
Interquartile range (IQR)0

Descriptive statistics

Standard deviation117.6714659
Coefficient of variation (CV)26.44993748
Kurtosis2299.158295
Mean4.448837204
Median Absolute Deviation (MAD)0
Skewness45.1069999
Sum2110604
Variance13846.57389
MonotocityNot monotonic
2021-03-06T17:07:54.098495image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0456734
96.3%
12681
 
0.1%
10562
 
0.1%
20500
 
0.1%
15440
 
0.1%
13411
 
0.1%
8405
 
0.1%
16381
 
0.1%
24378
 
0.1%
9377
 
0.1%
Other values (546)13548
 
2.9%
ValueCountFrequency (%)
0456734
96.3%
1263
 
0.1%
2120
 
< 0.1%
3132
 
< 0.1%
4199
 
< 0.1%
ValueCountFrequency (%)
123221
< 0.1%
109791
< 0.1%
103611
< 0.1%
98211
< 0.1%
80001
< 0.1%

ratings_count
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct789
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.142463276
Minimum0
Maximum4289
Zeros437847
Zeros (%)92.3%
Memory size3.6 MiB
2021-03-06T17:07:54.230942image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum4289
Range4289
Interquartile range (IQR)0

Descriptive statistics

Standard deviation36.55360595
Coefficient of variation (CV)17.06148542
Kurtosis2551.933788
Mean2.142463276
Median Absolute Deviation (MAD)0
Skewness41.89712863
Sum1016421
Variance1336.166108
MonotocityNot monotonic
2021-03-06T17:07:54.368358image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0437847
92.3%
113922
 
2.9%
24950
 
1.0%
32741
 
0.6%
41820
 
0.4%
51226
 
0.3%
6960
 
0.2%
7783
 
0.2%
8647
 
0.1%
9552
 
0.1%
Other values (779)8969
 
1.9%
ValueCountFrequency (%)
0437847
92.3%
113922
 
2.9%
24950
 
1.0%
32741
 
0.6%
41820
 
0.4%
ValueCountFrequency (%)
42891
< 0.1%
39391
< 0.1%
36131
< 0.1%
30501
< 0.1%
30331
< 0.1%

suggestions_count
Real number (ℝ≥0)

ZEROS

Distinct881
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.19684792
Minimum0
Maximum1839
Zeros37455
Zeros (%)7.9%
Memory size3.6 MiB
2021-03-06T17:07:54.507852image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116
median47
Q3122
95-th percentile350
Maximum1839
Range1839
Interquartile range (IQR)106

Descriptive statistics

Standard deviation116.4936952
Coefficient of variation (CV)1.263532299
Kurtosis5.529246977
Mean92.19684792
Median Absolute Deviation (MAD)38
Skewness2.168607923
Sum43739752
Variance13570.78103
MonotocityNot monotonic
2021-03-06T17:07:54.655281image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
037455
 
7.9%
96766
 
1.4%
86714
 
1.4%
106609
 
1.4%
116493
 
1.4%
76443
 
1.4%
66100
 
1.3%
126097
 
1.3%
135897
 
1.2%
145881
 
1.2%
Other values (871)379962
80.1%
ValueCountFrequency (%)
037455
7.9%
11549
 
0.3%
22288
 
0.5%
33422
 
0.7%
44630
 
1.0%
ValueCountFrequency (%)
18391
< 0.1%
14271
< 0.1%
13861
< 0.1%
13711
< 0.1%
12911
< 0.1%

game_series_count
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct25
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0442817184
Minimum0
Maximum28
Zeros471586
Zeros (%)99.4%
Memory size3.6 MiB
2021-03-06T17:07:54.790244image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum28
Range28
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7714720152
Coefficient of variation (CV)17.4219078
Kurtosis593.1175105
Mean0.0442817184
Median Absolute Deviation (MAD)0
Skewness22.75979028
Sum21008
Variance0.5951690703
MonotocityNot monotonic
2021-03-06T17:07:54.907981image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0471586
99.4%
1494
 
0.1%
2354
 
0.1%
3280
 
0.1%
4226
 
< 0.1%
7159
 
< 0.1%
9155
 
< 0.1%
6143
 
< 0.1%
19123
 
< 0.1%
8120
 
< 0.1%
Other values (15)777
 
0.2%
ValueCountFrequency (%)
0471586
99.4%
1494
 
0.1%
2354
 
0.1%
3280
 
0.1%
4226
 
< 0.1%
ValueCountFrequency (%)
2858
< 0.1%
2425
< 0.1%
2324
< 0.1%
2223
 
< 0.1%
2022
 
< 0.1%

reviews_count
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct790
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.162782953
Minimum0
Maximum4334
Zeros437152
Zeros (%)92.1%
Memory size3.6 MiB
2021-03-06T17:07:55.055335image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum4334
Range4334
Interquartile range (IQR)0

Descriptive statistics

Standard deviation36.86815954
Coefficient of variation (CV)17.04662944
Kurtosis2565.864351
Mean2.162782953
Median Absolute Deviation (MAD)0
Skewness41.98398272
Sum1026061
Variance1359.261188
MonotocityNot monotonic
2021-03-06T17:07:55.186446image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0437152
92.1%
114384
 
3.0%
25034
 
1.1%
32758
 
0.6%
41850
 
0.4%
51246
 
0.3%
6968
 
0.2%
7782
 
0.2%
8666
 
0.1%
9550
 
0.1%
Other values (780)9027
 
1.9%
ValueCountFrequency (%)
0437152
92.1%
114384
 
3.0%
25034
 
1.1%
32758
 
0.6%
41850
 
0.4%
ValueCountFrequency (%)
43341
< 0.1%
39961
< 0.1%
36451
< 0.1%
30691
< 0.1%
30531
< 0.1%

platforms
Categorical

HIGH CARDINALITY

Distinct5148
Distinct (%)1.1%
Missing3986
Missing (%)0.8%
Memory size3.6 MiB
PC
189284 
Web
90951 
iOS
57679 
Android
 
17516
Linux||macOS||PC
 
11082
Other values (5143)
103919 

Length

Max length245
Median length3
Mean length5.657618227
Min length2

Characters and Unicode

Total characters2661519
Distinct characters54
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3730 ?
Unique (%)0.8%

Sample

1st rowPC||macOS||Xbox One||PlayStation 4||Nintendo Switch
2nd rowmacOS||PC||Xbox One
3rd rowiOS
4th rowPC||PlayStation 4
5th rowPC
ValueCountFrequency (%)
PC189284
39.9%
Web90951
19.2%
iOS57679
 
12.2%
Android17516
 
3.7%
Linux||macOS||PC11082
 
2.3%
PC||macOS||Linux11015
 
2.3%
macOS||PC9924
 
2.1%
PC||macOS9431
 
2.0%
Web||PC6273
 
1.3%
Linux||PC3956
 
0.8%
Other values (5138)63320
 
13.3%
(Missing)3986
 
0.8%
2021-03-06T17:07:55.529064image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pc189284
37.0%
web90951
17.8%
ios57679
 
11.3%
android17516
 
3.4%
linux||macos||pc11082
 
2.2%
pc||macos||linux11015
 
2.2%
macos||pc9924
 
1.9%
pc||macos9431
 
1.8%
web||pc6273
 
1.2%
nintendo4885
 
1.0%
Other values (3048)102875
20.1%

Most occurring characters

ValueCountFrequency (%)
|339004
12.7%
P293959
 
11.0%
C280250
 
10.5%
i183667
 
6.9%
S157999
 
5.9%
e133626
 
5.0%
O133398
 
5.0%
b120153
 
4.5%
W115238
 
4.3%
n112015
 
4.2%
Other values (44)792210
29.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1156523
43.5%
Uppercase Letter1099577
41.3%
Math Symbol339004
 
12.7%
Space Separator40484
 
1.5%
Decimal Number23501
 
0.9%
Other Punctuation2132
 
0.1%
Dash Punctuation298
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
i183667
15.9%
e133626
11.6%
b120153
10.4%
n112015
9.7%
a98457
8.5%
d77742
6.7%
o71130
 
6.2%
m70936
 
6.1%
c68164
 
5.9%
x50435
 
4.4%
Other values (12)170198
14.7%
ValueCountFrequency (%)
P293959
26.7%
C280250
25.5%
S157999
14.4%
O133398
12.1%
W115238
 
10.5%
L42882
 
3.9%
A38870
 
3.5%
N10180
 
0.9%
X7729
 
0.7%
D4618
 
0.4%
Other values (10)14454
 
1.3%
ValueCountFrequency (%)
38153
34.7%
45752
24.5%
03476
14.8%
63323
14.1%
22220
 
9.4%
8351
 
1.5%
5173
 
0.7%
753
 
0.2%
ValueCountFrequency (%)
|339004
100.0%
ValueCountFrequency (%)
40484
100.0%
ValueCountFrequency (%)
/2132
100.0%
ValueCountFrequency (%)
-298
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2256100
84.8%
Common405419
 
15.2%

Most frequent character per script

ValueCountFrequency (%)
P293959
13.0%
C280250
12.4%
i183667
 
8.1%
S157999
 
7.0%
e133626
 
5.9%
O133398
 
5.9%
b120153
 
5.3%
W115238
 
5.1%
n112015
 
5.0%
a98457
 
4.4%
Other values (32)627338
27.8%
ValueCountFrequency (%)
|339004
83.6%
40484
 
10.0%
38153
 
2.0%
45752
 
1.4%
03476
 
0.9%
63323
 
0.8%
22220
 
0.5%
/2132
 
0.5%
8351
 
0.1%
-298
 
0.1%
Other values (2)226
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2661519
100.0%

Most frequent character per block

ValueCountFrequency (%)
|339004
12.7%
P293959
 
11.0%
C280250
 
10.5%
i183667
 
6.9%
S157999
 
5.9%
e133626
 
5.0%
O133398
 
5.0%
b120153
 
4.5%
W115238
 
4.3%
n112015
 
4.2%
Other values (44)792210
29.8%

developers
Categorical

HIGH CARDINALITY
MISSING

Distinct213723
Distinct (%)45.9%
Missing8366
Missing (%)1.8%
Memory size3.6 MiB
Sony Interactive Entertainment
 
397
Big Fish Games
 
373
SEGA
 
348
Konami Digital Entertainment
 
317
Nintendo
 
290
Other values (213718)
464326 

Length

Max length1096
Median length11
Mean length12.74404518
Min length1

Characters and Unicode

Total characters5939375
Distinct characters1762
Distinct categories22 ?
Distinct scripts15 ?
Distinct blocks31 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141732 ?
Unique (%)30.4%

Sample

1st rowWest Coast Software
2nd rowSoma Games
3rd rowPrettygreat Pty
4th rowOasis Games||Geronimo Interactive
5th rowViking Tao
ValueCountFrequency (%)
Sony Interactive Entertainment397
 
0.1%
Big Fish Games373
 
0.1%
SEGA348
 
0.1%
Konami Digital Entertainment317
 
0.1%
Nintendo290
 
0.1%
Capcom282
 
0.1%
Robert Brooks239
 
0.1%
Square Enix209
 
< 0.1%
Bandai Namco Entertainment172
 
< 0.1%
HAMSTER170
 
< 0.1%
Other values (213713)463254
97.6%
(Missing)8366
 
1.8%
2021-03-06T17:07:56.627915image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
games30574
 
4.1%
studios9664
 
1.3%
studio7099
 
1.0%
entertainment5643
 
0.8%
software4100
 
0.6%
game3795
 
0.5%
interactive3583
 
0.5%
the2904
 
0.4%
2856
 
0.4%
digital1844
 
0.2%
Other values (201964)667778
90.3%

Most occurring characters

ValueCountFrequency (%)
e504363
 
8.5%
a495673
 
8.3%
i361909
 
6.1%
o355019
 
6.0%
n317243
 
5.3%
r308289
 
5.2%
274050
 
4.6%
t272271
 
4.6%
s260444
 
4.4%
l207984
 
3.5%
Other values (1752)2582130
43.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4451493
74.9%
Uppercase Letter962908
 
16.2%
Space Separator274083
 
4.6%
Decimal Number104399
 
1.8%
Math Symbol94604
 
1.6%
Other Punctuation21058
 
0.4%
Connector Punctuation11368
 
0.2%
Dash Punctuation9594
 
0.2%
Other Letter6655
 
0.1%
Other Symbol897
 
< 0.1%
Other values (12)2316
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
153
 
2.3%
146
 
2.2%
146
 
2.2%
143
 
2.1%
142
 
2.1%
141
 
2.1%
128
 
1.9%
121
 
1.8%
118
 
1.8%
105
 
1.6%
Other values (1230)5312
79.8%
ValueCountFrequency (%)
e504363
11.3%
a495673
11.1%
i361909
 
8.1%
o355019
 
8.0%
n317243
 
7.1%
r308289
 
6.9%
t272271
 
6.1%
s260444
 
5.9%
l207984
 
4.7%
m180815
 
4.1%
Other values (166)1187483
26.7%
ValueCountFrequency (%)
S101961
 
10.6%
G84452
 
8.8%
A66412
 
6.9%
M59781
 
6.2%
T55264
 
5.7%
C53714
 
5.6%
D51378
 
5.3%
B43709
 
4.5%
E43466
 
4.5%
P43352
 
4.5%
Other values (110)359419
37.3%
ValueCountFrequency (%)
301
33.6%
©208
23.2%
117
 
13.0%
®63
 
7.0%
¦53
 
5.9%
13
 
1.4%
°10
 
1.1%
9
 
1.0%
9
 
1.0%
8
 
0.9%
Other values (43)106
 
11.8%
ValueCountFrequency (%)
.12432
59.0%
'2119
 
10.1%
&1371
 
6.5%
,1217
 
5.8%
"837
 
4.0%
!772
 
3.7%
@681
 
3.2%
/497
 
2.4%
:362
 
1.7%
?109
 
0.5%
Other values (28)661
 
3.1%
ValueCountFrequency (%)
35
19.9%
33
18.8%
21
11.9%
18
10.2%
14
 
8.0%
ˆ11
 
6.2%
11
 
6.2%
11
 
6.2%
3
 
1.7%
2
 
1.1%
Other values (14)17
9.7%
ValueCountFrequency (%)
̷52
19.5%
̶21
 
7.9%
̴21
 
7.9%
̇15
 
5.6%
̻15
 
5.6%
͝15
 
5.6%
͖15
 
5.6%
̿15
 
5.6%
̭15
 
5.6%
̕15
 
5.6%
Other values (8)67
25.2%
ValueCountFrequency (%)
|94200
99.6%
+184
 
0.2%
~83
 
0.1%
<34
 
< 0.1%
>30
 
< 0.1%
=17
 
< 0.1%
15
 
< 0.1%
±14
 
< 0.1%
13
 
< 0.1%
×6
 
< 0.1%
Other values (7)8
 
< 0.1%
ValueCountFrequency (%)
³52
31.7%
¼38
23.2%
¾17
 
10.4%
½17
 
10.4%
²16
 
9.8%
10
 
6.1%
5
 
3.0%
4
 
2.4%
¹3
 
1.8%
1
 
0.6%
ValueCountFrequency (%)
118560
17.8%
016366
15.7%
214460
13.9%
311246
10.8%
98783
8.4%
48345
8.0%
77561
7.2%
56865
 
6.6%
86598
 
6.3%
65615
 
5.4%
ValueCountFrequency (%)
(350
59.4%
[143
24.3%
33
 
5.6%
28
 
4.8%
{23
 
3.9%
9
 
1.5%
2
 
0.3%
1
 
0.2%
ValueCountFrequency (%)
$30
21.6%
¢29
20.9%
£25
18.0%
20
14.4%
¥17
12.2%
¤16
11.5%
1
 
0.7%
1
 
0.7%
ValueCountFrequency (%)
¸37
23.4%
^33
20.9%
´27
17.1%
`24
15.2%
˜23
14.6%
¨10
 
6.3%
¯4
 
2.5%
ValueCountFrequency (%)
)370
67.4%
]143
 
26.0%
}22
 
4.0%
10
 
1.8%
2
 
0.4%
2
 
0.4%
ValueCountFrequency (%)
-9556
99.6%
18
 
0.2%
17
 
0.2%
2
 
< 0.1%
1
 
< 0.1%
ValueCountFrequency (%)
­64
75.3%
16
 
18.8%
3
 
3.5%
1
 
1.2%
1
 
1.2%
ValueCountFrequency (%)
38
40.9%
36
38.7%
10
 
10.8%
»9
 
9.7%
ValueCountFrequency (%)
34
38.2%
27
30.3%
«20
22.5%
8
 
9.0%
ValueCountFrequency (%)
274050
> 99.9%
 29
 
< 0.1%
 4
 
< 0.1%
ValueCountFrequency (%)
ि3
50.0%
3
50.0%
ValueCountFrequency (%)
1
50.0%
1
50.0%
ValueCountFrequency (%)
_11368
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5410207
91.1%
Common517944
 
8.7%
Han5279
 
0.1%
Cyrillic4236
 
0.1%
Katakana563
 
< 0.1%
Hiragana422
 
< 0.1%
Inherited260
 
< 0.1%
Hangul212
 
< 0.1%
Greek97
 
< 0.1%
Arabic90
 
< 0.1%
Other values (5)65
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
153
 
2.9%
146
 
2.8%
146
 
2.8%
143
 
2.7%
142
 
2.7%
141
 
2.7%
128
 
2.4%
121
 
2.3%
118
 
2.2%
105
 
2.0%
Other values (1008)3936
74.6%
ValueCountFrequency (%)
e504363
 
9.3%
a495673
 
9.2%
i361909
 
6.7%
o355019
 
6.6%
n317243
 
5.9%
r308289
 
5.7%
t272271
 
5.0%
s260444
 
4.8%
l207984
 
3.8%
m180815
 
3.3%
Other values (211)2146197
39.7%
ValueCountFrequency (%)
274050
52.9%
|94200
 
18.2%
118560
 
3.6%
016366
 
3.2%
214460
 
2.8%
.12432
 
2.4%
_11368
 
2.2%
311246
 
2.2%
-9556
 
1.8%
98783
 
1.7%
Other values (182)46923
 
9.1%
ValueCountFrequency (%)
27
 
12.7%
13
 
6.1%
13
 
6.1%
9
 
4.2%
6
 
2.8%
6
 
2.8%
5
 
2.4%
5
 
2.4%
5
 
2.4%
5
 
2.4%
Other values (58)118
55.7%
ValueCountFrequency (%)
43
 
7.6%
29
 
5.2%
29
 
5.2%
29
 
5.2%
26
 
4.6%
22
 
3.9%
21
 
3.7%
20
 
3.6%
19
 
3.4%
18
 
3.2%
Other values (56)307
54.5%
ValueCountFrequency (%)
и340
 
8.0%
а310
 
7.3%
е290
 
6.8%
о254
 
6.0%
р246
 
5.8%
т235
 
5.5%
л228
 
5.4%
н220
 
5.2%
в193
 
4.6%
к167
 
3.9%
Other values (55)1753
41.4%
ValueCountFrequency (%)
49
 
11.6%
33
 
7.8%
33
 
7.8%
25
 
5.9%
21
 
5.0%
16
 
3.8%
15
 
3.6%
14
 
3.3%
12
 
2.8%
12
 
2.8%
Other values (42)192
45.5%
ValueCountFrequency (%)
ن9
 
10.0%
ا9
 
10.0%
د7
 
7.8%
ی7
 
7.8%
ل5
 
5.6%
و5
 
5.6%
ع5
 
5.6%
ه5
 
5.6%
ب4
 
4.4%
م4
 
4.4%
Other values (15)30
33.3%
ValueCountFrequency (%)
Λ28
28.9%
Ξ15
15.5%
α9
 
9.3%
ι6
 
6.2%
Δ6
 
6.2%
σ5
 
5.2%
π4
 
4.1%
ε3
 
3.1%
ν2
 
2.1%
θ2
 
2.1%
Other values (14)17
17.5%
ValueCountFrequency (%)
̷52
20.0%
̶21
 
8.1%
̴21
 
8.1%
̇15
 
5.8%
̻15
 
5.8%
͝15
 
5.8%
͖15
 
5.8%
̿15
 
5.8%
̭15
 
5.8%
̕15
 
5.8%
Other values (6)61
23.5%
ValueCountFrequency (%)
9
30.0%
3
 
10.0%
3
 
10.0%
3
 
10.0%
3
 
10.0%
3
 
10.0%
ि3
 
10.0%
3
 
10.0%
ValueCountFrequency (%)
ה10
50.0%
י5
25.0%
ו5
25.0%
ValueCountFrequency (%)
4
50.0%
4
50.0%
ValueCountFrequency (%)
2
100.0%
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5920101
99.7%
None6971
 
0.1%
CJK5279
 
0.1%
Cyrillic4236
 
0.1%
Katakana594
 
< 0.1%
Hiragana422
 
< 0.1%
Punctuation357
 
< 0.1%
Specials301
 
< 0.1%
Diacriticals260
 
< 0.1%
Hangul212
 
< 0.1%
Other values (21)642
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
e504363
 
8.5%
a495673
 
8.4%
i361909
 
6.1%
o355019
 
6.0%
n317243
 
5.4%
r308289
 
5.2%
274050
 
4.6%
t272271
 
4.6%
s260444
 
4.4%
l207984
 
3.5%
Other values (87)2562856
43.3%
ValueCountFrequency (%)
é843
 
12.1%
Ã694
 
10.0%
í383
 
5.5%
á365
 
5.2%
ó219
 
3.1%
©208
 
3.0%
ğ185
 
2.7%
Ÿ176
 
2.5%
ç164
 
2.4%
ı153
 
2.2%
Other values (214)3581
51.4%
ValueCountFrequency (%)
153
 
2.9%
146
 
2.8%
146
 
2.8%
143
 
2.7%
142
 
2.7%
141
 
2.7%
128
 
2.4%
121
 
2.3%
118
 
2.2%
105
 
2.0%
Other values (1008)3936
74.6%
ValueCountFrequency (%)
43
 
7.2%
35
 
5.9%
29
 
4.9%
29
 
4.9%
29
 
4.9%
26
 
4.4%
22
 
3.7%
21
 
3.5%
20
 
3.4%
19
 
3.2%
Other values (54)321
54.0%
ValueCountFrequency (%)
117
95.1%
4
 
3.3%
1
 
0.8%
1
 
0.8%
ValueCountFrequency (%)
9
25.7%
9
25.7%
6
17.1%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
ValueCountFrequency (%)
38
10.6%
36
10.1%
34
9.5%
33
9.2%
31
8.7%
28
 
7.8%
27
 
7.6%
24
 
6.7%
18
 
5.0%
18
 
5.0%
Other values (9)70
19.6%
ValueCountFrequency (%)
8
30.8%
6
23.1%
5
19.2%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
ValueCountFrequency (%)
20
90.9%
1
 
4.5%
1
 
4.5%
ValueCountFrequency (%)
13
22.8%
8
14.0%
8
14.0%
6
10.5%
4
 
7.0%
4
 
7.0%
3
 
5.3%
3
 
5.3%
2
 
3.5%
2
 
3.5%
Other values (4)4
 
7.0%
ValueCountFrequency (%)
301
100.0%
ValueCountFrequency (%)
15
48.4%
13
41.9%
1
 
3.2%
1
 
3.2%
1
 
3.2%
ValueCountFrequency (%)
27
 
12.7%
13
 
6.1%
13
 
6.1%
9
 
4.2%
6
 
2.8%
6
 
2.8%
5
 
2.4%
5
 
2.4%
5
 
2.4%
5
 
2.4%
Other values (58)118
55.7%
ValueCountFrequency (%)
˜23
52.3%
ˆ11
25.0%
ˢ2
 
4.5%
ʳ1
 
2.3%
ʷ1
 
2.3%
ʸ1
 
2.3%
ː1
 
2.3%
ˋ1
 
2.3%
ˏ1
 
2.3%
ˎ1
 
2.3%
ValueCountFrequency (%)
2
40.0%
1
20.0%
1
20.0%
1
20.0%
ValueCountFrequency (%)
15
22.4%
14
20.9%
11
16.4%
11
16.4%
3
 
4.5%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
Other values (3)3
 
4.5%
ValueCountFrequency (%)
ɪ7
33.3%
ʀ6
28.6%
ʙ5
23.8%
ʟ2
 
9.5%
ɛ1
 
4.8%
ValueCountFrequency (%)
̷52
20.0%
̶21
 
8.1%
̴21
 
8.1%
̇15
 
5.8%
̻15
 
5.8%
͝15
 
5.8%
͖15
 
5.8%
̿15
 
5.8%
̭15
 
5.8%
̕15
 
5.8%
Other values (6)61
23.5%
ValueCountFrequency (%)
и340
 
8.0%
а310
 
7.3%
е290
 
6.8%
о254
 
6.0%
р246
 
5.8%
т235
 
5.5%
л228
 
5.4%
н220
 
5.2%
в193
 
4.6%
к167
 
3.9%
Other values (55)1753
41.4%
ValueCountFrequency (%)
49
 
11.6%
33
 
7.8%
33
 
7.8%
25
 
5.9%
21
 
5.0%
16
 
3.8%
15
 
3.6%
14
 
3.3%
12
 
2.8%
12
 
2.8%
Other values (42)192
45.5%
ValueCountFrequency (%)
21
95.5%
1
 
4.5%
ValueCountFrequency (%)
ن9
 
10.0%
ا9
 
10.0%
د7
 
7.8%
ی7
 
7.8%
ل5
 
5.6%
و5
 
5.6%
ع5
 
5.6%
ه5
 
5.6%
ب4
 
4.4%
م4
 
4.4%
Other values (15)30
33.3%
ValueCountFrequency (%)
3
23.1%
3
23.1%
3
23.1%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
ValueCountFrequency (%)
9
30.0%
3
 
10.0%
3
 
10.0%
3
 
10.0%
3
 
10.0%
3
 
10.0%
ि3
 
10.0%
3
 
10.0%
ValueCountFrequency (%)
ה10
50.0%
י5
25.0%
ו5
25.0%
ValueCountFrequency (%)
2
100.0%
ValueCountFrequency (%)
5
100.0%
ValueCountFrequency (%)
4
50.0%
4
50.0%
ValueCountFrequency (%)
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
ValueCountFrequency (%)
5
71.4%
1
 
14.3%
1
 
14.3%
ValueCountFrequency (%)
4
100.0%

genres
Categorical

HIGH CARDINALITY
MISSING

Distinct1968
Distinct (%)0.5%
Missing103185
Missing (%)21.7%
Memory size3.6 MiB
Action
45464 
Platformer
34158 
Puzzle
32337 
Adventure
28169 
Shooter
 
19276
Other values (1963)
211828 

Length

Max length185
Median length10
Mean length11.92895278
Min length3

Characters and Unicode

Total characters4428409
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique775 ?
Unique (%)0.2%

Sample

1st rowAdventure||Puzzle
2nd rowSimulation||Indie
3rd rowAdventure||Arcade
4th rowAction||Indie
5th rowRPG||Strategy||Massively Multiplayer
ValueCountFrequency (%)
Action45464
 
9.6%
Platformer34158
 
7.2%
Puzzle32337
 
6.8%
Adventure28169
 
5.9%
Shooter19276
 
4.1%
Simulation16599
 
3.5%
Strategy13615
 
2.9%
RPG11434
 
2.4%
Action||Shooter7075
 
1.5%
Arcade6183
 
1.3%
Other values (1958)156922
33.1%
(Missing)103185
21.7%
2021-03-06T17:07:56.981176image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
action45464
 
11.9%
platformer34158
 
9.0%
puzzle32337
 
8.5%
adventure28169
 
7.4%
shooter19276
 
5.1%
simulation16599
 
4.4%
strategy13615
 
3.6%
rpg11434
 
3.0%
action||shooter7075
 
1.9%
arcade6183
 
1.6%
Other values (1814)166716
43.8%

Most occurring characters

ValueCountFrequency (%)
t392999
 
8.9%
|386308
 
8.7%
e380589
 
8.6%
o285472
 
6.4%
r285304
 
6.4%
n278392
 
6.3%
i263021
 
5.9%
a261366
 
5.9%
u206697
 
4.7%
A196486
 
4.4%
Other values (23)1491775
33.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3394231
76.6%
Uppercase Letter638076
 
14.4%
Math Symbol386308
 
8.7%
Space Separator9794
 
0.2%

Most frequent character per category

ValueCountFrequency (%)
t392999
11.6%
e380589
11.2%
o285472
8.4%
r285304
8.4%
n278392
 
8.2%
i263021
 
7.7%
a261366
 
7.7%
u206697
 
6.1%
l192605
 
5.7%
c148294
 
4.4%
Other values (10)699492
20.6%
ValueCountFrequency (%)
A196486
30.8%
P135754
21.3%
S121357
19.0%
R48413
 
7.6%
G39453
 
6.2%
I33157
 
5.2%
C32276
 
5.1%
F11542
 
1.8%
E7555
 
1.2%
B7505
 
1.2%
ValueCountFrequency (%)
|386308
100.0%
ValueCountFrequency (%)
9794
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4032307
91.1%
Common396102
 
8.9%

Most frequent character per script

ValueCountFrequency (%)
t392999
 
9.7%
e380589
 
9.4%
o285472
 
7.1%
r285304
 
7.1%
n278392
 
6.9%
i263021
 
6.5%
a261366
 
6.5%
u206697
 
5.1%
A196486
 
4.9%
l192605
 
4.8%
Other values (21)1289376
32.0%
ValueCountFrequency (%)
|386308
97.5%
9794
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII4428409
100.0%

Most frequent character per block

ValueCountFrequency (%)
t392999
 
8.9%
|386308
 
8.7%
e380589
 
8.6%
o285472
 
6.4%
r285304
 
6.4%
n278392
 
6.3%
i263021
 
5.9%
a261366
 
5.9%
u206697
 
4.7%
A196486
 
4.4%
Other values (23)1491775
33.7%

publishers
Categorical

HIGH CARDINALITY
MISSING

Distinct45452
Distinct (%)32.2%
Missing333384
Missing (%)70.3%
Memory size3.6 MiB
Nintendo
 
994
Electronic Arts
 
948
Ubisoft Entertainment
 
859
SEGA
 
852
Big Fish Games
 
777
Other values (45447)
136603 

Length

Max length430
Median length13
Mean length15.2910879
Min length1

Characters and Unicode

Total characters2156548
Distinct characters1259
Distinct categories20 ?
Distinct scripts9 ?
Distinct blocks16 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31425 ?
Unique (%)22.3%

Sample

1st rowWest Coast Software
2nd rowImmanitas Entertainment||Code-Monkeys
3rd rowPrettygreat Pty
4th rowGeronimo Interactive
5th rowViking Tao
ValueCountFrequency (%)
Nintendo994
 
0.2%
Electronic Arts948
 
0.2%
Ubisoft Entertainment859
 
0.2%
SEGA852
 
0.2%
Big Fish Games777
 
0.2%
Konami578
 
0.1%
Activision Blizzard534
 
0.1%
Capcom441
 
0.1%
Square Enix371
 
0.1%
Bandai Namco Entertainment335
 
0.1%
Other values (45442)134344
28.3%
(Missing)333384
70.3%
2021-03-06T17:07:57.387795image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
games16805
 
5.6%
entertainment6327
 
2.1%
studios4710
 
1.6%
interactive4160
 
1.4%
studio3461
 
1.2%
software2751
 
0.9%
co1928
 
0.6%
nguyen1786
 
0.6%
game1654
 
0.6%
technology1581
 
0.5%
Other values (42794)255065
85.0%

Most occurring characters

ValueCountFrequency (%)
e168886
 
7.8%
a163013
 
7.6%
159269
 
7.4%
i135748
 
6.3%
n122977
 
5.7%
o115114
 
5.3%
t113615
 
5.3%
r96496
 
4.5%
s83535
 
3.9%
m64917
 
3.0%
Other values (1249)932978
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1487691
69.0%
Uppercase Letter459441
 
21.3%
Space Separator159271
 
7.4%
Math Symbol26162
 
1.2%
Other Punctuation8819
 
0.4%
Decimal Number7611
 
0.4%
Other Letter3959
 
0.2%
Dash Punctuation2439
 
0.1%
Connector Punctuation342
 
< 0.1%
Close Punctuation313
 
< 0.1%
Other values (10)500
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
114
 
2.9%
98
 
2.5%
95
 
2.4%
95
 
2.4%
94
 
2.4%
94
 
2.4%
94
 
2.4%
93
 
2.3%
90
 
2.3%
87
 
2.2%
Other values (958)3005
75.9%
ValueCountFrequency (%)
e168886
11.4%
a163013
11.0%
i135748
 
9.1%
n122977
 
8.3%
o115114
 
7.7%
t113615
 
7.6%
r96496
 
6.5%
s83535
 
5.6%
m64917
 
4.4%
l58604
 
3.9%
Other values (101)364786
24.5%
ValueCountFrequency (%)
S45973
 
10.0%
G37712
 
8.2%
A35645
 
7.8%
E30766
 
6.7%
T27583
 
6.0%
M25191
 
5.5%
I24492
 
5.3%
C22645
 
4.9%
N20948
 
4.6%
P19409
 
4.2%
Other values (68)169077
36.8%
ValueCountFrequency (%)
.5327
60.4%
,1423
 
16.1%
'722
 
8.2%
&691
 
7.8%
/186
 
2.1%
!132
 
1.5%
:110
 
1.2%
"90
 
1.0%
;40
 
0.5%
?28
 
0.3%
Other values (18)70
 
0.8%
ValueCountFrequency (%)
48
44.4%
28
25.9%
®15
 
13.9%
©6
 
5.6%
2
 
1.9%
2
 
1.9%
2
 
1.9%
2
 
1.9%
1
 
0.9%
°1
 
0.9%
ValueCountFrequency (%)
11361
17.9%
21266
16.6%
3994
13.1%
0818
10.7%
5768
10.1%
4625
8.2%
7547
7.2%
8544
 
7.1%
9356
 
4.7%
6332
 
4.4%
ValueCountFrequency (%)
|26069
99.6%
+48
 
0.2%
=30
 
0.1%
±5
 
< 0.1%
~5
 
< 0.1%
>2
 
< 0.1%
×1
 
< 0.1%
<1
 
< 0.1%
¬1
 
< 0.1%
ValueCountFrequency (%)
(281
90.4%
[12
 
3.9%
9
 
2.9%
{3
 
1.0%
3
 
1.0%
2
 
0.6%
1
 
0.3%
ValueCountFrequency (%)
)285
91.1%
]13
 
4.2%
10
 
3.2%
}3
 
1.0%
2
 
0.6%
ValueCountFrequency (%)
¸10
58.8%
`2
 
11.8%
˜2
 
11.8%
´2
 
11.8%
^1
 
5.9%
ValueCountFrequency (%)
¼2
33.3%
²1
16.7%
¾1
16.7%
³1
16.7%
¹1
16.7%
ValueCountFrequency (%)
159269
> 99.9%
 1
 
< 0.1%
 1
 
< 0.1%
ValueCountFrequency (%)
­1
33.3%
1
33.3%
1
33.3%
ValueCountFrequency (%)
10
52.6%
8
42.1%
1
 
5.3%
ValueCountFrequency (%)
8
61.5%
4
30.8%
«1
 
7.7%
ValueCountFrequency (%)
¢8
47.1%
8
47.1%
$1
 
5.9%
ValueCountFrequency (%)
-2436
99.9%
3
 
0.1%
ValueCountFrequency (%)
2
50.0%
»2
50.0%
ValueCountFrequency (%)
1
50.0%
1
50.0%
ValueCountFrequency (%)
_342
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1945558
90.2%
Common205457
 
9.5%
Han3689
 
0.2%
Cyrillic1561
 
0.1%
Hiragana124
 
< 0.1%
Katakana97
 
< 0.1%
Hangul41
 
< 0.1%
Greek13
 
< 0.1%
Arabic8
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
114
 
3.1%
98
 
2.7%
95
 
2.6%
95
 
2.6%
94
 
2.5%
94
 
2.5%
94
 
2.5%
93
 
2.5%
90
 
2.4%
87
 
2.4%
Other values (847)2735
74.1%
ValueCountFrequency (%)
e168886
 
8.7%
a163013
 
8.4%
i135748
 
7.0%
n122977
 
6.3%
o115114
 
5.9%
t113615
 
5.8%
r96496
 
5.0%
s83535
 
4.3%
m64917
 
3.3%
l58604
 
3.0%
Other values (112)822653
42.3%
ValueCountFrequency (%)
159269
77.5%
|26069
 
12.7%
.5327
 
2.6%
-2436
 
1.2%
,1423
 
0.7%
11361
 
0.7%
21266
 
0.6%
3994
 
0.5%
0818
 
0.4%
5768
 
0.4%
Other values (92)5726
 
2.8%
ValueCountFrequency (%)
и173
 
11.1%
е132
 
8.5%
о119
 
7.6%
а87
 
5.6%
в77
 
4.9%
р76
 
4.9%
К72
 
4.6%
с71
 
4.5%
т67
 
4.3%
л67
 
4.3%
Other values (45)620
39.7%
ValueCountFrequency (%)
13
 
10.5%
10
 
8.1%
8
 
6.5%
8
 
6.5%
7
 
5.6%
7
 
5.6%
6
 
4.8%
6
 
4.8%
6
 
4.8%
4
 
3.2%
Other values (29)49
39.5%
ValueCountFrequency (%)
8
 
8.2%
6
 
6.2%
6
 
6.2%
4
 
4.1%
4
 
4.1%
4
 
4.1%
4
 
4.1%
4
 
4.1%
4
 
4.1%
4
 
4.1%
Other values (25)49
50.5%
ValueCountFrequency (%)
4
 
9.8%
3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
1
 
2.4%
Other values (19)19
46.3%
ValueCountFrequency (%)
ε2
15.4%
Σ1
7.7%
μ1
7.7%
ι1
7.7%
ό1
7.7%
ν1
7.7%
Ο1
7.7%
ύ1
7.7%
γ1
7.7%
λ1
7.7%
Other values (2)2
15.4%
ValueCountFrequency (%)
ن1
12.5%
ق1
12.5%
ش1
12.5%
ا1
12.5%
ل1
12.5%
ض1
12.5%
و1
12.5%
ء1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2150141
99.7%
CJK3689
 
0.2%
Cyrillic1561
 
0.1%
None747
 
< 0.1%
Hiragana124
 
< 0.1%
Katakana110
 
< 0.1%
Specials48
 
< 0.1%
Hangul41
 
< 0.1%
Punctuation31
 
< 0.1%
Letterlike Symbols29
 
< 0.1%
Other values (6)27
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
e168886
 
7.9%
a163013
 
7.6%
159269
 
7.4%
i135748
 
6.3%
n122977
 
5.7%
o115114
 
5.4%
t113615
 
5.3%
r96496
 
4.5%
s83535
 
3.9%
m64917
 
3.0%
Other values (87)926571
43.1%
ValueCountFrequency (%)
é98
 
13.1%
ö39
 
5.2%
ü32
 
4.3%
ğ28
 
3.7%
í26
 
3.5%
ø26
 
3.5%
ł25
 
3.3%
á22
 
2.9%
ô22
 
2.9%
ı21
 
2.8%
Other values (105)408
54.6%
ValueCountFrequency (%)
114
 
3.1%
98
 
2.7%
95
 
2.6%
95
 
2.6%
94
 
2.5%
94
 
2.5%
94
 
2.5%
93
 
2.5%
90
 
2.4%
87
 
2.4%
Other values (847)2735
74.1%
ValueCountFrequency (%)
13
 
10.5%
10
 
8.1%
8
 
6.5%
8
 
6.5%
7
 
5.6%
7
 
5.6%
6
 
4.8%
6
 
4.8%
6
 
4.8%
4
 
3.2%
Other values (29)49
39.5%
ValueCountFrequency (%)
28
96.6%
1
 
3.4%
ValueCountFrequency (%)
ن1
12.5%
ق1
12.5%
ش1
12.5%
ا1
12.5%
ل1
12.5%
ض1
12.5%
و1
12.5%
ء1
12.5%
ValueCountFrequency (%)
и173
 
11.1%
е132
 
8.5%
о119
 
7.6%
а87
 
5.6%
в77
 
4.9%
р76
 
4.9%
К72
 
4.6%
с71
 
4.5%
т67
 
4.3%
л67
 
4.3%
Other values (45)620
39.7%
ValueCountFrequency (%)
8
25.8%
4
12.9%
3
 
9.7%
3
 
9.7%
3
 
9.7%
2
 
6.5%
2
 
6.5%
1
 
3.2%
1
 
3.2%
1
 
3.2%
Other values (3)3
 
9.7%
ValueCountFrequency (%)
10
 
9.1%
8
 
7.3%
6
 
5.5%
6
 
5.5%
4
 
3.6%
4
 
3.6%
4
 
3.6%
4
 
3.6%
4
 
3.6%
4
 
3.6%
Other values (26)56
50.9%
ValueCountFrequency (%)
48
100.0%
ValueCountFrequency (%)
2
50.0%
2
50.0%
ValueCountFrequency (%)
4
 
9.8%
3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
1
 
2.4%
Other values (19)19
46.3%
ValueCountFrequency (%)
2
66.7%
1
33.3%
ValueCountFrequency (%)
2
100.0%
ValueCountFrequency (%)
˜2
100.0%
ValueCountFrequency (%)
8
100.0%

esrb_rating
Categorical

MISSING

Distinct6
Distinct (%)< 0.1%
Missing418553
Missing (%)88.2%
Memory size3.6 MiB
Everyone 10+
36682 
Teen
10031 
Mature
4859 
Everyone
3837 
Adults Only
 
405

Length

Max length14
Median length12
Mean length9.761438493
Min length4

Characters and Unicode

Total characters545313
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEveryone 10+
2nd rowEveryone
3rd rowEveryone 10+
4th rowTeen
5th rowTeen
ValueCountFrequency (%)
Everyone 10+36682
 
7.7%
Teen10031
 
2.1%
Mature4859
 
1.0%
Everyone3837
 
0.8%
Adults Only405
 
0.1%
Rating Pending50
 
< 0.1%
(Missing)418553
88.2%
2021-03-06T17:07:58.040794image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-03-06T17:07:58.130920image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
everyone40519
43.6%
1036682
39.4%
teen10031
 
10.8%
mature4859
 
5.2%
adults405
 
0.4%
only405
 
0.4%
pending50
 
0.1%
rating50
 
0.1%

Most occurring characters

ValueCountFrequency (%)
e106009
19.4%
n51105
9.4%
r45378
8.3%
y40924
 
7.5%
E40519
 
7.4%
v40519
 
7.4%
o40519
 
7.4%
37137
 
6.8%
136682
 
6.7%
036682
 
6.7%
Other values (15)69839
12.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter341811
62.7%
Decimal Number73364
 
13.5%
Uppercase Letter56319
 
10.3%
Space Separator37137
 
6.8%
Math Symbol36682
 
6.7%

Most frequent character per category

ValueCountFrequency (%)
e106009
31.0%
n51105
15.0%
r45378
13.3%
y40924
 
12.0%
v40519
 
11.9%
o40519
 
11.9%
t5314
 
1.6%
u5264
 
1.5%
a4909
 
1.4%
l810
 
0.2%
Other values (4)1060
 
0.3%
ValueCountFrequency (%)
E40519
71.9%
T10031
 
17.8%
M4859
 
8.6%
A405
 
0.7%
O405
 
0.7%
R50
 
0.1%
P50
 
0.1%
ValueCountFrequency (%)
136682
50.0%
036682
50.0%
ValueCountFrequency (%)
37137
100.0%
ValueCountFrequency (%)
+36682
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin398130
73.0%
Common147183
 
27.0%

Most frequent character per script

ValueCountFrequency (%)
e106009
26.6%
n51105
12.8%
r45378
11.4%
y40924
 
10.3%
E40519
 
10.2%
v40519
 
10.2%
o40519
 
10.2%
T10031
 
2.5%
t5314
 
1.3%
u5264
 
1.3%
Other values (11)12548
 
3.2%
ValueCountFrequency (%)
37137
25.2%
136682
24.9%
036682
24.9%
+36682
24.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII545313
100.0%

Most frequent character per block

ValueCountFrequency (%)
e106009
19.4%
n51105
9.4%
r45378
8.3%
y40924
 
7.5%
E40519
 
7.4%
v40519
 
7.4%
o40519
 
7.4%
37137
 
6.8%
136682
 
6.7%
036682
 
6.7%
Other values (15)69839
12.8%

added_status_yet
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct343
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6850302582
Minimum0
Maximum635
Zeros450434
Zeros (%)94.9%
Memory size3.6 MiB
2021-03-06T17:07:58.252944image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum635
Range635
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.012424022
Coefficient of variation (CV)13.15624225
Kurtosis1040.250813
Mean0.6850302582
Median Absolute Deviation (MAD)0
Skewness27.88984876
Sum324990
Variance81.22378675
MonotocityNot monotonic
2021-03-06T17:07:58.390022image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0450434
94.9%
19151
 
1.9%
23347
 
0.7%
31919
 
0.4%
41226
 
0.3%
5853
 
0.2%
6670
 
0.1%
7517
 
0.1%
8416
 
0.1%
9394
 
0.1%
Other values (333)5490
 
1.2%
ValueCountFrequency (%)
0450434
94.9%
19151
 
1.9%
23347
 
0.7%
31919
 
0.4%
41226
 
0.3%
ValueCountFrequency (%)
6351
< 0.1%
5511
< 0.1%
5381
< 0.1%
5331
< 0.1%
5321
< 0.1%

added_status_owned
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct1861
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.25141806
Minimum0
Maximum8298
Zeros415331
Zeros (%)87.5%
Memory size3.6 MiB
2021-03-06T17:07:58.526781image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum8298
Range8298
Interquartile range (IQR)0

Descriptive statistics

Standard deviation128.531595
Coefficient of variation (CV)11.42359073
Kurtosis834.7987795
Mean11.25141806
Median Absolute Deviation (MAD)0
Skewness24.63380046
Sum5337864
Variance16520.37091
MonotocityNot monotonic
2021-03-06T17:07:58.664169image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0415331
87.5%
118334
 
3.9%
26435
 
1.4%
34356
 
0.9%
42520
 
0.5%
51556
 
0.3%
61119
 
0.2%
7869
 
0.2%
8792
 
0.2%
9621
 
0.1%
Other values (1851)22484
 
4.7%
ValueCountFrequency (%)
0415331
87.5%
118334
 
3.9%
26435
 
1.4%
34356
 
0.9%
42520
 
0.5%
ValueCountFrequency (%)
82981
< 0.1%
78211
< 0.1%
77081
< 0.1%
75061
< 0.1%
72991
< 0.1%

added_status_beaten
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct634
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.361485781
Minimum0
Maximum3533
Zeros447076
Zeros (%)94.2%
Memory size3.6 MiB
2021-03-06T17:07:58.807432image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum3533
Range3533
Interquartile range (IQR)0

Descriptive statistics

Standard deviation28.51972469
Coefficient of variation (CV)20.94750094
Kurtosis3576.23793
Mean1.361485781
Median Absolute Deviation (MAD)0
Skewness50.7065118
Sum645912
Variance813.3746965
MonotocityNot monotonic
2021-03-06T17:07:58.948792image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0447076
94.2%
110452
 
2.2%
24741
 
1.0%
32185
 
0.5%
41289
 
0.3%
5911
 
0.2%
6702
 
0.1%
7516
 
0.1%
8415
 
0.1%
9373
 
0.1%
Other values (624)5757
 
1.2%
ValueCountFrequency (%)
0447076
94.2%
110452
 
2.2%
24741
 
1.0%
32185
 
0.5%
41289
 
0.3%
ValueCountFrequency (%)
35331
< 0.1%
34141
< 0.1%
30881
< 0.1%
28201
< 0.1%
27591
< 0.1%

added_status_toplay
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct294
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4307666041
Minimum0
Maximum2325
Zeros446474
Zeros (%)94.1%
Memory size3.6 MiB
2021-03-06T17:07:59.090163image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum2325
Range2325
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.970948356
Coefficient of variation (CV)20.82554282
Kurtosis13549.54129
Mean0.4307666041
Median Absolute Deviation (MAD)0
Skewness85.48676318
Sum204363
Variance80.47791441
MonotocityNot monotonic
2021-03-06T17:07:59.227566image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0446474
94.1%
114297
 
3.0%
25853
 
1.2%
31891
 
0.4%
41076
 
0.2%
5661
 
0.1%
6492
 
0.1%
7340
 
0.1%
8253
 
0.1%
9234
 
< 0.1%
Other values (284)2846
 
0.6%
ValueCountFrequency (%)
0446474
94.1%
114297
 
3.0%
25853
 
1.2%
31891
 
0.4%
41076
 
0.2%
ValueCountFrequency (%)
23251
< 0.1%
12311
< 0.1%
11731
< 0.1%
10921
< 0.1%
9031
< 0.1%

added_status_dropped
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct368
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6780996465
Minimum0
Maximum1092
Zeros450536
Zeros (%)95.0%
Memory size3.6 MiB
2021-03-06T17:07:59.367116image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1092
Range1092
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.48497671
Coefficient of variation (CV)15.4622949
Kurtosis2233.273319
Mean0.6780996465
Median Absolute Deviation (MAD)0
Skewness38.93530996
Sum321702
Variance109.9347366
MonotocityNot monotonic
2021-03-06T17:07:59.528011image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0450536
95.0%
19791
 
2.1%
23294
 
0.7%
31797
 
0.4%
41214
 
0.3%
5819
 
0.2%
6686
 
0.1%
7503
 
0.1%
8466
 
0.1%
9376
 
0.1%
Other values (358)4935
 
1.0%
ValueCountFrequency (%)
0450536
95.0%
19791
 
2.1%
23294
 
0.7%
31797
 
0.4%
41214
 
0.3%
ValueCountFrequency (%)
10921
< 0.1%
10561
< 0.1%
9881
< 0.1%
8691
< 0.1%
8381
< 0.1%

added_status_playing
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct188
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1490271217
Minimum0
Maximum644
Zeros464939
Zeros (%)98.0%
Memory size3.6 MiB
2021-03-06T17:07:59.674252image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum644
Range644
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.911149012
Coefficient of variation (CV)26.24454507
Kurtosis7678.888013
Mean0.1490271217
Median Absolute Deviation (MAD)0
Skewness72.95285179
Sum70701
Variance15.29708659
MonotocityNot monotonic
2021-03-06T17:07:59.800847image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0464939
98.0%
15072
 
1.1%
21303
 
0.3%
3622
 
0.1%
4397
 
0.1%
5256
 
0.1%
6197
 
< 0.1%
7174
 
< 0.1%
8127
 
< 0.1%
9106
 
< 0.1%
Other values (178)1224
 
0.3%
ValueCountFrequency (%)
0464939
98.0%
15072
 
1.1%
21303
 
0.3%
3622
 
0.1%
4397
 
0.1%
ValueCountFrequency (%)
6441
< 0.1%
6421
< 0.1%
5591
< 0.1%
4971
< 0.1%
4151
< 0.1%

Interactions

2021-03-06T17:06:59.822541image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:00.041593image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:00.349217image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:00.530366image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:00.720555image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:00.890911image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:01.080844image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:01.268091image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:01.431535image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:01.614764image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:01.793821image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:01.990193image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:02.158208image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:02.321946image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:02.431686image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:02.533663image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:02.635605image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:02.750899image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:02.869972image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:02.976387image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:03.094701image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:03.205052image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:03.315009image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:03.426651image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:03.534433image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:03.652608image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:03.763001image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:03.881382image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:04.064671image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:04.171482image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:04.338268image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:04.629696image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:04.804745image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:04.970587image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:05.167025image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:05.326611image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:05.509579image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:05.686433image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:05.846022image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:06.008729image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:06.165158image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:06.349535image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:06.539239image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:06.659958image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:06.817784image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:06.983257image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:07.161099image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:07.351660image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:07.535311image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:07.709937image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:07.895247image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:08.079596image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-06T17:07:08.262963image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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Correlations

2021-03-06T17:07:59.944530image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-03-06T17:08:00.191044image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-03-06T17:08:00.434940image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-03-06T17:08:00.728267image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-03-06T17:08:00.944275image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-03-06T17:07:38.214262image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
A simple visualization of nullity by column.
2021-03-06T17:07:40.162562image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-03-06T17:07:43.337264image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-03-06T17:07:43.991549image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idslugnamemetacriticreleasedtbaupdatedwebsiteratingrating_topplaytimeachievements_countratings_countsuggestions_countgame_series_countreviews_countplatformsdevelopersgenrespublishersesrb_ratingadded_status_yetadded_status_ownedadded_status_beatenadded_status_toplayadded_status_droppedadded_status_playing
01dgeneration-hdD/Generation HDNaN2015-10-23False2019-09-17T11:58:57http://dgeneration.net0.00180229204PC||macOS||Xbox One||PlayStation 4||Nintendo SwitchWest Coast SoftwareAdventure||PuzzleWest Coast SoftwareEveryone 10+4882200
110g-primeG Prime Into The RainNaN2016-01-06False2019-11-06T23:04:19NaN0.00026338903macOS||PC||Xbox OneSoma GamesSimulation||IndieImmanitas Entertainment||Code-MonkeysEveryone2422000
2100land-slidersLand SlidersNaN2015-09-24False2019-10-22T13:56:16http://prettygreat.com0.000028302iOSPrettygreat PtyAdventure||ArcadePrettygreat PtyEveryone 10+022010
31000pixel-gearPixel GearNaN2016-10-20False2019-08-28T22:16:02https://www.facebook.com/Geronimo-Interactive-1789605664633280/?ref=bookmarks0.0000045500PC||PlayStation 4Oasis Games||Geronimo InteractiveAction||IndieGeronimo InteractiveTeen010000
410000gods-and-idolsGods and IdolsNaN2016-12-12False2019-09-17T13:37:13http://www.godsandidols.com/0.0110526205PCViking TaoRPG||Strategy||Massively MultiplayerViking TaoNaN2790000
5100000plague-venuePlague venueNaN2017-12-02False2019-01-09T12:41:06NaN0.000004000WebAlexander PonomariovNaNNaNNaN000000
6100001the-moon-sliver-itchThe Moon Sliver (itch)NaN2014-05-03False2019-01-09T12:41:06NaN0.0000011600PC||macOSDavid SzymanskiAdventureNaNNaN000000
7100002red-entityRed EntityNaN2014-08-26False2019-01-09T12:41:06NaN0.000003900PC||macOS||LinuxwoofAction||ShooterNaNNaN000000
8100004hippiesvscopsHippiesVsCopsNaN2016-04-18False2019-08-28T23:25:11NaN0.000002600PCalegaroficialStrategyNaNNaN000000
9100005they-came-through-the-floorThey Came Through the FloorNaN2018-06-24False2019-01-09T12:41:06NaN0.000009800PCAtte OkkonenPlatformerNaNNaN000000

Last rows

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